Center for Bioinformatics Saarland University Module Descriptions

Center for Bioinformatics
Saarland University
Module Descriptions
Master Program Bioinformatics
October 2011
Core Lectures of Computer Science ................................................................................3
Advanced Lectures of Life Sciences ..............................................................................25
Advanced Lectures of Bioinformatics .............................................................................43
Lectures to achieve Key Qualifications...........................................................................57
Advanced Practical Training of Life Sciences ................................................................63
Tutor ...............................................................................................................................64
Seminar ..........................................................................................................................66
Master Seminar ..............................................................................................................68
Master Thesis .................................................................................................................69
Module Descriptions of the Master Program Bioinformatics, Saarland University
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Compulsory courses:
A compulsory course must be taken to gain the relevant qualification.
Mandatory Elective Courses:
Mandatory elective courses give students a restricted choice. Students
must complete a certain number of mandatory elective courses from a set
of options to fulfil a certain category given by the examination regulations.
Elective Courses:
Not all courses chosen need necessarily come from the degree program
being studied. Some courses offered by other faculties in the UdS can be
used to contribute credit points towards the final degree.
Module Descriptions of the Master Program Bioinformatics, Saarland University
2
Module: Core Lectures Computer Science
Program of Studies:
Master Program Bioinformatics
Name of the module:
Data Structures and Algorithms
Abbreviation:
I-M-1
Subtitle:
Core lecture
Modules:
Semester:
Lecture 4 h (weekly)
Tutorial 2 h (weekly)
1st -3rd Semester / at least once every two years
Responsible lecturer:
Prof. Dr. Kurt Mehlhorn
Lecturer:
Prof. Dr. Kurt Mehlhorn, Prof. Dr. R. Seidel, Dr. Ernst Althaus,
Dr. Ulrich Meyer
English
Language:
Level of the unit/
Mandatory or not
Course type/weekly
hours:
Graduate course / mandatory elective
Total workload:
270 h = 90 h of classes and 180 h private study
Credits:
9
Entrance requirements:
For graduate students: C, C++, Java
.
Aims/Competences to
be developed:
The students know standard algorithms for typical problems in
the areas graphs, computational geometry, strings and
optimization. Furthermore they master a number of methods and
data-structures to develop efficient algorithms and analyze their
running times.
Lecture 4 h (weekly)
Tutorial 2 h (weekly)
Tutorials in groups of up to 20 students
Module Descriptions of the Master Program Bioinformatics, Saarland University
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Content:
- graph algorithms (shortest path, minimum spanning trees,
maximal flows, matchings, etc.)
- computational geometry (convex hull, Delaunay
triangulation, Voronoi diagram, intersection of line
segments, etc.)
- strings (pattern matching, suffix trees, etc.)
- generic methods of optimization (tabu search, simulated
annealing, genetic algorithms, linear programming, branchand-bound, dynamic programming, approximation
algorithms, etc.)
- data-structures (Fibonacci heaps, radix heaps, hashing,
randomized search trees, segment trees, etc.)
- methods for analyzing algorithms (amortized analysis,
average-case analysis, potential methods, etc.)
Assessment/Exams:
- Regular attendance of classes and tutorials
- Passing the midterm and the final exam
A re-exam takes place during the last two weeks before the start
of lectures in the following semester
Used media:
Literature:
Slides, beamer
- Cormen, Leiserson, Rivest and Stein, Introduction to
Algorithms, Mc Graw Hill, 2001
- Aho, Hopcroft, Ullman, The Design and Analysis of
Computer Algorithms, Addison-Wesley, 1974.
- Mehlhorn, Näher, LEDA, A platform for combinatorial and
geometric computing, Cambridge Univ. Press, 1999.
- Tarjan, Data Structures and Network Algorithms, SIAM,
1983.
- Mehlhorn, Data Structures and Algorithms, Vol 1-3,
Springer Verlag, 1984.
- Knuth, The Art of Computer Programming, Addison
Wesley.
Module Descriptions of the Master Program Bioinformatics, Saarland University
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Program of Studies:
Master Program Bioinformatics
Name of the module:
Computer Graphics
Abbreviation:
I-M-2
Subtitle:
Core lecture
Modules:
Semester:
Lecture 4 h (weekly)
Tutorial 2 h (weekly)
1st -3rd Semester / at least once every two years
Responsible lecturer:
Prof. Dr. Philipp Slusallek
Lecturer:
Prof. Dr. Philipp Slusallek, Prof. Dr. Hans-Peter Seidel, Dr.
Marcus Magnor
English
Language:
Level of the unit/
Mandatory or not
Course type/weekly
hours:
Graduate course / mandatory elective
Total workload:
270 h = 90 h of classes and 180 h private study
Credits:
9
Entrance requirements:
For graduate students: none
.
Aims/Competences to
be developed:
This course provides the theoretical and practical foundation for
computer graphics. It gives a wide overview of topics,
techniques, and approaches used in various aspects of computer
graphics but focuses on image synthesis or rendering. After
introducing of physical background and the representations used
in graphics it discusses the two basic algorithms for image
synthesis: ray tracing and rasterization. In the context we present
related topics like texturing, shading, aliasing, sampling, and
many more. As part of the practical exercises the students
incrementally build their own ray tracing system or hardwarebased visualization application. A final rendering competition
allows students to implement their favorite advanced algorithm
and use it in a high-quality rendering.
Lecture 4 h (weekly)
Tutorial 2 h (weekly)
Tutorials in groups of up to 20 students
Module Descriptions of the Master Program Bioinformatics, Saarland University
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Content:
Fundamental of digital image synthesis
- Physical laws of light transport
- Human visual system
- Colors and Tone-Mapping
- Signal processing and anti-aliasing
- Materials and reflection models
- Geometric modeling
- Camera models
Ray Tracing
-
Recursive ray tracing algorithm
Spatial index structures
Sampling approaches
Parallel and distributed algorithms
Rasterization and graphics hardware
-
Assessment/exams:
Homogeneous coordinates
Hardware architectures
Rendering pipeline
Shader programming and languages
OpenGL
- Successful completion of at least 50% of the exercises
- Successful participation in rendering competition
- Final written exam
Fianl grade determined by result of the exam and the rendering
competition.
A re-exam takes place during the last two weeks before the start
of the lectures in the following semester.
Used media:
Electronic slides, examples, live presentations
Pratical excersises on a 3D graphics PC
Development of an individual extension to ray tracing and/or
OpenGL algorithms
Literature:
- Alan Watt, 3D Computer Graphics, Addison-Wesley, 1999
- James Foley, AndriesVan Dam, et al., Computer Graphics :
Principles and Practice, 2. Edition, Addison-Wesley, 1995
- Andrew Glassner, Principles of Digital Image Synthesis, 2
Volumes, Morgan Kaufman, 1996
- Peter Shirley, Realistic Ray-Tracing, AK Peters
- Andrew Woo, et al., OpenGL Programming Guide, 3. Edition,
Addison-Wesley, 1999
- Randima Fernando, GPU Gems, Addison-Wesley, 2004
Module Descriptions of the Master Program Bioinformatics, Saarland University
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Program of Studies:
Master Program Bioinformatics
Name of the module:
Database Systems
Abbreviation:
I-M-3
Subtitle:
Core lecture
Modules:
Semester:
Lecture 4 h (weekly)
Tutorial 2 h (weekly)
1st -3rd Semester / at least once every two years
Responsible lecturer:
Prof. Dr. Jens Dittrich
Lecturer:
Prof. Dr. Jens Dittrich, Prof. Dr. Gerhard Weikum
Language:
English
Level of the unit/
Mandatory or not
Course type/weekly
hours:
Graduate course / mandatory elective
Total workload:
270 h = 90 h of classes and 180 h private study
Credits:
9
Entrance requirements:
Especially Information Systems
For graduate students:
- motivation for databases and database management systems;
- the relational data model;
- relational query languages, particularly relational algebra and
SQL; XML;
- solid programming skills in C/C++ (e.g. from "Software Design
Practical").
Lecture 4 h (weekly)
Tutorial 2 h (weekly)
Tutorials in groups of up to 20 students
Module Descriptions of the Master Program Bioinformatics, Saarland University
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Aims/Competences to
be developed:
Database systems are the backbone of most modern information
systems and a core technology without which today's economy -as well as many other aspects of our lifes -- would be impossible
in their present forms. The course teaches the architectural and
algorithmic foundations of modern database management
systems (DBMS), focussing on database systems internals
rather than applications. Emphasis is made on robust and timetested techniques that have led databases to be considered a
mature technology and one of the greatest success stories in
computer science. At the same time, opportunities for exciting
research in this field will be pointed out. In the exercise part of
the course, a DBMS kernel will be implemented and its
performance evaluated. The goal of this implementation project
is to work with the techniques introduced in the lectures and to
understand them and their practical implications to a depth that
would not be attainable by purely theoretical study. Moreover, an
important goal of this project - and the course as a whole - is to
communicate the essential difference between being a mere
programmer and being a systems expert: The techniques taught
in the course should allow the participant, starting the
implementation project with a naive prototype, to attain query
processing performance improvements of many orders of
magnitude, far beyond what could be achieved by good
programming alone.
Content:
The course "Database Systems" will introduce students to
the internal workings of a DBMS, in particular
- physical storage; disks, pages, records, clustering
- tree- and hash-indexes
- query processing: sorting on disk, pipelined evaluation, nestedloop-,
- hash- and merge-joins, ...
- query optimization (algebraic query rewriting, join reordering,
- selectivity estimations, histograms and cost-based
optimization)
- database tuning
- transactions; concurrency control and recovery
- distributed databases: vertical and horizontal partitioning,
distributed
- query evaluation and optimization, distributed transaction
management
- (two-phase commit, ...), redundancy
- XML-, object-oriented-, and object-relational databases
Module Descriptions of the Master Program Bioinformatics, Saarland University
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Assessment/Exams
- Passing a two-hour written exam at the end of the semester
- Successful demonstration of programming project (teams of 2
students are allowed)
Grades are based on written exam (100 points); successful
demonstration of the programming project is a requirement for
the admission to the exam. It is possible to obtain up to ca. 20
bonus points for the programming project (for efficient
implementations and the implementation of advanced query
optimization techniques)
A re-exam takes place during the last two weeks before the start
of lectures in the following semester.
Used Media:
Slides, beamer, blackboard, table PC
Literature:
Ramakrishnan and Gehrke, Database Management Systems,
3rd Edition, McGraw-Hill 2002 (ISBN 0-07-115110-9) - English.
or
Kemper/Eickler, "Datenbanksysteme", 5th edition, Oldenbourg
Verlag - German
Module Descriptions of the Master Program Bioinformatics, Saarland University
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Program of Studies:
Master Program Bioinformatics
Name of the module:
Information Retrival and Data Mining
Abbreviation:
I-M-4
Subtitle:
Core lecture
Modules:
Semester:
Lecture 4 h (weekly)
Tutorial 2 h (weekly)
1st -3rd Semester / at least once every two years
Responsible lecturer:
Prof. Dr. Gerhard Weikum
Lecturer:
Prof. Dr. Gerhard Weikum
Language:
English
Level of the unit/
Mandatory or not
Course type/weekly
hours:
Graduate course / mandatory elective
Total workload:
270 h = 90 h of classes and 180 h private study
Credits:
9
Entrance requirements:
For graduate students: none
Aims/Competences to
be developed:
The lecture teaches mathematical models and algorithms that
form the basis for search engines for the Web, intranets, and
digital libraries and for data mining and analysis tools.
Content:
Information Retrieval and Data Mining are technologies for
searching, analyzing and automatically organizing text
documents, multi-media documents, and structured or
semistructured data. The course teaches mathematical models
and algorithms that form the basis for search engines for the
Web, intranets, and digital libraries and for data mining and
analysis tools. The fundamentals are models and methods from
linear algebra and regression (e.g. singular-value decomposition)
as well as probability theory and statistics (e.g. Bayesian
networks and Markov chains). The exercises include practical
tasks for the implementation of a simple search engine in Java.
Lecture 4 h (weekly)
Tutorial 2 h (weekly)
Tutorials in groups of up to 20 students
Module Descriptions of the Master Program Bioinformatics, Saarland University
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Assessment/Exams:
-
Regular attendance of classes and tutorials
Passing 2 of 3 written exams (midterm, final and re-exam)
Presentation of a solution during a tutorial (at least once)
For each additional presentation up to 3 bonus points can be
gained
- Passing the practical exercises (teams of up to two students)
- Up to 3 bonus points can be gained fort he overall quality of the
solutions
A re-exam takes place during the last two weeks before the start
of lectures in the following semester.
Used Media:
- Slides, beamer, blackboard
Literature:
Information Retrieval:
- C.D. Manning, H. Schütze: Foundations of Statistical Natural
Language Processing, MIT Press, 1999
- S. Chakrabarti: Mining the Web: Analysis of Hypertext and
Semistructured Data, Morgan Kaufmann, 2002
- R. Baeza-Yates, B. Ribeiro-Neto: Modern Information
Retrieval, Addison-Wesley, 1999.
- N. Fuhr: Information Retrieval, Skriptum zur Vorlesung im SS
2002, Uni Dortmund.
Data Mining:
- J. Han, M. Kamber: Data Mining: Concepts and Techniques,
Morgan Kaufmann, 2000
- R.O. Duda, P.E. Hart, D.G. Stork: Pattern Classification, John
Wiley & Sons, 2001
Java:
- Go To Java 2
- Thinking in Java
Module Descriptions of the Master Program Bioinformatics, Saarland University
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Program of Studies:
Master Program Bioinformatics
Name of the module:
Artificial Intelligence
Abbreviation:
I-M-5
Subtitle:
Core lecture
Modules:
Lecture 4 h (weekly)
Tutorial 2 h (weekly)
Semester:
1st -3rd Semester / At least once every two years
Responsible lecturer:
Prof. Dr. Wolfgang Wahlster
Lecturer:
Prof. Dr. Wolfgang Wahlster, Prof. Dr. Jörg Siekmann, Dr. Serge
Autexier
Language:
English
Level of the unit/
Mandatory or not :
Graduate course / mandatory elective
Course type/weekly
hours:
Lecture 4 h (weekly)
Tutorial 2 h (weekly)
Tutorials in groups of up to 20 students
Total workload:
270 h = 90 h of classes and 180 h private study
Credits:
9
Entrance requirements:
For graduate students: none
Aims/Competences to
be developed:
Knowledge about the fundamentals of artificial intelligence
Module Descriptions of the Master Program Bioinformatics, Saarland University
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Content:
Problem-solving:
– Uninformed- and informed search procedures
– Adversarial search
– Knowledge and reasoning:
– First-order logic, Inference in first-order logic
– Knowledge representation
Planning:
– Planning
– Planning and acting in the real world
Uncertain knowledge and reasoning:
– Uncertainty
– Probabilistic reasoning
– Simple & complex decisions
Learning:
– Learning from observations
– Knowledge in learning
– Statistical learning methods
– Reinforcement learning
Communicating, perceiving, and acting:
– Communication
– Natural language processing
– Perception
Assessment/Exams:
• Regular attendance of classes and tutorials
• Solving of weekly assignments
• Passing the final written exam
A re-exam takes place during the last two weeks before the start
of lectures in the following semester.
Used media:
Slides, beamer, blackboard during classes, printouts and
assignments at the WWW, practical assignments (Computer)
Literature:
An updated list of used literature will be issued at the beginning
of the semester.
•
S. Russell, P. Norvig: Artificial Intelligence – A Modern
Approach (2nd Edition), Prentice Hall Series in AI
Module Descriptions of the Master Program Bioinformatics, Saarland University
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Program of Studies:
Master Program Bioinformatics
Name of the module:
Optimization
Abbreviation:
I-M-6
Subtitle:
Core lecture
Modules:
Lecture 4 h (weekly)
Tutorial 2 h (weekly)
Semester:
1st -3rd Semester / At least once every two years
Responsible lecturer:
Dean Computer Science
Lecturer:
Dr. Fritz Eisenbrand
Language:
English
Level of the unit/
Mandatory or not :
Graduate course / mandatory elective
Course type/weekly
hours:
Lecture 4 h (weekly)
Tutorial 2 h (weekly)
Tutorials in groups of up to 20 students
Total workload:
270 h = 90 h of classes and 180 h private study
Credits:
9
Entrance requirements:
For graduate students: none
Aims/Competences to
be developed:
The students learn to model and solve optimization problems
from theory as from the real world
Content:
- Linear Programming: Theory of polyhedra, simplex algorithm,
duality, ellipsoid method
- Integer linear programming: Branch-and-Bound, cutting planes,
TDI-Systems
- Network flow: Minimum cost network flow, minimum mean
cycle cancellation algorithm, network simplex method
- Matchings in graphs: Polynomial matching algorithms in
general graphs, integrality of the matching polytope, cutting
planes
- Approximation algorithms: LP-Rounding, greedy methods,
knapsack, bin packing, steiner trees and forests, survivable
network design
Module Descriptions of the Master Program Bioinformatics, Saarland University
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Assessment/Exams:
- Regular attendance of classes and tutorials
- Solving accompanying exercises, successful partcipation in
midterm and final exam
- Grades: Yes
- The grade is calculated from the above parameters according
to the following scheme: 20%, 30%, 50%
A re-exam takes place during the last two weeks before the start
of lectures in the following semester
Used media:
Practical exercises supplement the theoretical exercises. The
lecture is accompanied with a difficult real-world optimization
problem which is solved by the students in teams within the
scope of an optimization contest.
Literature:
- Bernhard Korte, Jens Vygen: Combinatorial Optimization,
Theory and Algorithms, Springer Verlag, 2001
- Alexander Schrijver: Theory of Linear and Integer
- Programming, Wiley-Interscience, 1986
- Alexander Schrijver: Combinatorial Optimization, Springer
Verlag, 2002
Module Descriptions of the Master Program Bioinformatics, Saarland University
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Program of Studies:
Master Program Bioinformatics
Name of the module:
Geometric Modelling
Abbreviation:
I-M-7
Subtitle:
Core lecture
Modules:
Lecture 4 h (weekly)
Tutorial 2 h (weekly)
Semester:
1st -3rd Semester / At least once every two years
Responsible lecturer:
Prof. Dr. Hans-Peter Seidel
Lecturer:
Prof. Dr. Hans-Peter Seidel, Prof. Dr. Philipp Slusallek
Language:
English
Level of the unit/
Mandatory or not :
Graduate course / mandatory elective
Course type/weekly
hours:
Lecture 4 h (weekly)
Tutorial 2 h (weekly)
Tutorials in groups of up to 20 students
Total worload:
270 h = 90 h of classes and 180 h private study
Credits:
9
Entrance requirements:
For graduate students: none
Aims/Competences to
be developed:
Learning working knowledge of theoretical and practical methods
for solving geometric modeling problems on a computer.
Module Descriptions of the Master Program Bioinformatics, Saarland University
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Content:
-
Polynomial Curves
Bezier and Rational Bezier Curves
B-splines, NURBS
Tensor Product Surfaces
Shape Interrogation Methods
Mesh Processing
Multiresolution Modeling
Assessment/Exams:
-
Regular attendance of classes and tutorials
Weekly Assignments (40%)
Midterm exam (20%)
Final exam (40%)
A re-exam takes place during the last two weeks before the start of
lectures in the following semester.
Used media:
Slides, beamer
Literature:
- G. Farin. Curves and surfaces for Computer-Aided Geometric
Design, Academic Press
- J. Hoschek and D. Lasser. Grundlagen der geometrischen
Datenverarbeitung, Teubner (original German version)
Fundamentals of computer aided geometric design, AK Peters
(English translation)
- C. de Boor. A practical Guide to Splines, Springer
- N. Dyn. Analysis of Convergence and Smoothness by the
Formalism of Laurent Polynomials. In: A. Iske, E. Quak, M. S.
Floater. Tutorials on multiresolution in geometric modelling:
summer school lecture notes.
- J. Warren and H. Weimer. Subdivision methods for geometric
design: a constructive approach.
- P. Schröder, D. Zorin. Subdivision for modelling and animation.
SIGGRAPH 2000 course notes
Module Descriptions of the Master Program Bioinformatics, Saarland University
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Program of Studies:
Master Program Bioinformatics
Name of the module:
Introduction to Computational Logic
Abbreviation:
I-M-8
Subtitle:
Core lecture
Modules:
Lecture 4 h (weekly)
Tutorial 2 h (weekly)
Semester:
1st -3rd Semester / At least once every two years
Responsible lecturer:
Prof. Dr. Gert Smolka
Lecturer:
Prof. Dr. Gert Smolka
Language:
English
Level of the unit/
Mandatory or not :
Graduate course / mandatory elective
Course type/weekly
hours:
Lecture 4 h (weekly)
Tutorial 2 h (weekly)
Tutorials in groups of up to 20 students
Total worload:
270 h = 90 h of classes and 180 h private study
Credits:
9
Entrance requirements:
For graduate students: none
Aims/Competences to
be developed:
- structure of logic languages based on type theory
- distinction notation / syntax / semantics
- structure and formal representation of mathematical
statements
- structure and formal representation of proofs (equational and
natural deduction)
- solving Boolean equations
- proving formulas with quantifiers
- implementing syntax and deduction
Module Descriptions of the Master Program Bioinformatics, Saarland University
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Content:
Type Theory
- functional representation of mathematical statements
- simply typed lambda calculus, De Bruijn representation and
substitution, normalization, elimination of lambdas
- Interpretations and semantic consequence
- Equational deduction, soundness and completeness
- Propositional Logic
- Boolean Axioms, completeness for 2-valued interpretation
- resolution of Boolean equations, canonical forms based on
decision trees and resolution
Predicate Logic (higher-order)
- quantifier axioms
- natural deduction
- prenex and Skolem forms
Assessment/Exams:
- Regular attendance of classes and tutorials
- Passing the midterm and the final exam
Used media:
Slides, beamer, excercises on paper and at the computer
Literature:
Script for the lecture
Propositional and predicate logic
- Uwe Schöning, Logik für Informatiker, 5. Auflage, Spektrum
Akademischer Verlag, 2000.
- L.T.F. Gamut, Logic, language and meaning, Volume 1:
Introduction to logic Univ. Chicago Press, 1991
- Willard V. Quine, Methods of Logic. 4th edition, Harward
University Press, 1982
- Melvin Fitting, First-Order Logic and Automated Theorem Proving,
2nd edition, Springer-Verlag, 1996
- Jean H. Gallier, Logic for Computer Science, Foundations of
Automatic Theorem Proving, Harper & Row, 1986
Type theory
- Peter B. Andrews, An Introduction to Mathematical Logic and
Type Theory: To Truth Through Proof, Kluwer Academic
Publishers, 2002
- J. Roger Hindley, Basic Simple Type Theory, Cambridge
University Press, 1997
- Fairouz Kamareddine, Twan Laan and Rob Nederpelt, A Modern
Perspective on Type Theory From its Origins Until Today, Kluwer,
2004
- John C. Mitchell, Foundations for Programming Languages, The
MIT Press, 1996
History and philosophie of logic
- J.N. Crossley, et al., What is Mathematical Logic? Dover
Publications, 1990, Christos H. Papadimitriou
- Turing (A Novel about Computation), The MIT Press, 2003
Module Descriptions of the Master Program Bioinformatics, Saarland University
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Program of Studies:
Master Program Bioinformatics
Name of the module:
Image Processing and Computer Vision
Abbreviation:
I-M-9
Subtitle:
Core lecture
Modules:
Lecture 4 h (weekly)
Tutorial 2 h (weekly)
Responsible lecturer:
1st -3rd Semester / At least once every two years
Lecturer:
Prof. Dr. Joachim Weickert
Language:
Prof. Dr. Joachim Weickert
Sprache:
English
Level of the unit/
Mandatory or not :
Graduate course / mandatory elective
Course type/weekly
hours:
Total workload:
Lecture 4 h (weekly)
Tutorial 2 h (weekly)
Tutorials in groups of up to 20 students
270 h = 90 h of classes and 180 h private study
Credits:
9
Entrance requirements:
For graduate students: none
Aims/Competences to
be developed:
Broad introduction to mathematical methods in image processing
and computer vision. The lecture qualifies students for a bachelor
thesis in this field. Together with the completion of advanced or
specialised lectures (9 credits at least) it is the basis for a master
thesis in this field.
Module Descriptions of the Master Program Bioinformatics, Saarland University
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Content:
1. Basics
1.1 Image Types and Discretisation
1.2 Degradations in Digital Images
2. Image Transformations
2.1 Fourier Transform
2.2 Image Pyramids
2.3 Wavelet Transform
3. Colour Perception and Colour Spaces
4. Image Enhancement
4.1 Point Operations
4.2 Linear Filtering
4.3 Wavelet Shrinkage, Median Filtering, M-Smoothers
4.4 Mathematical Morphology
4.5 Diffusion Filtering
4.6 Variational Methods
4.7 Deblurring
5. Feature Extraction
5.1 Edges
5.2 Corners
5.3 Lines and Circles
6. Texture Analysis
7. Segmentation
7.1 Classical Methods
7.2 Variational Methods
8. Image Sequence Analysis
8.1 Local Methods
8.2 Variational Methods
9. 3-D Reconstruction
9.1 Camera Geometry
9.2 Stereo
9.3 Shape-from-Shading
10. Object Recognition
10.1 Eigenspace Methods
10.2 Moment Invariances
Assessment/Exams:
- Regular attendance of classes and tutorials.
- At least 50% of all possible points from the weekly assignments
have to be gained to qualify for the final exam.
- Passing the final exam
A re-exam takes place during the last two weeks before the start
of lectures in the following semester.
Used media:
Slides, beamer
Module Descriptions of the Master Program Bioinformatics, Saarland University
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Literature:
- R. C. Gonzalez, R. E. Woods: Digital Image Processing.
Addison-Wesley, Second Edition, 2002.
- K. R. Castleman: Digital Image Processing. Prentice Hall,
Englewood Cliffs, 1996.
- R. Jain, R. Kasturi, B. G. Schunck: Machine Vision. McGraw-
Hill, New York, 1995.
- R. Klette, K. Schlüns, A. Koschan: Computer Vision: Three-
Dimensional Data from Images. Springer, Singapore, 1998.
- E. Trucco, A. Verri: Introductory Techniques for 3-D Computer
Vision. Prentice Hill, Upper Saddle River, 1998.
Module Descriptions of the Master Program Bioinformatics, Saarland University
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Program of Studies:
Master Program Bioinformatics
Name of the module:
Software Engineering
Abbreviation:
I-M-10
Subtitle:
Core lecture
Modules:
Lecture 4 h (weekly)
Tutorial 2 h (weekly)
Semester:
1st -3rd Semester / At least once every two years
Responsible lecturer:
Prof. Dr. Andreas Zeller
Lecturer:
Prof. Dr. Andreas Zeller
Language:
English
Level of the unit/
Mandatory or not :
Graduate course / mandatory elective
Course type/weekly
hours:
Lecture 4 h (weekly)
Tutorial 2 h (weekly)
Tutorials in groups of up to 20 students
Total workload:
270 h = 90 h of classes and 180 h private study
Credits:
9
Entrance requirements:
For graduate students: none
Aims/Competences to
be developed:
The students know and apply modern software development
techniques
They are aware of advanced quality assurance techniques such
as test coverage, program analysis, and verification and know
about the appropriate standards.
They know modern paradigms of programming and design, and
know when to use them.
They know the standards of project management and project
organization and can assess the state of given projects as well
as suggest consequences to reach specific targets.
Module Descriptions of the Master Program Bioinformatics, Saarland University
23
Content:
- Software Processes (Testing process, ISO 9000, maturity
model, extreme programming)
- Modeling and design (requirements engineering, formal
specification, proofs, model checking)
- Programming paradigms (aspect-oriented, generative, and
component-based programming)
- Validation (Testing, Reliability assessment, tools)
- Software maintenance (configuration management,
reengineering, restructuring)
- Project skills (organization, structure, estimations)
- Human resources (communication, assessment) Controlling
(metrics, change requests, risk and quality managament)
Assessment/Exams:
- Regular attendance of classes and tutorials
- Passing the final exam
A re-exam takes place during the last two weeks before the start
of lectures in the following semester.
Used Media:
Slides, beamer, presentations with laptop, labs using computer
Literature:
- Balzert, Softwaretechnik I and II
- Own lecture notes
Module Descriptions of the Master Program Bioinformatics, Saarland University
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Module: Advanced Lectures of Life Sciences
Program of Studies:
Master Program Bioinformatics
Name of the module:
Molecular Biotechnology 2
Abbreviation:
B-M-1
Subtitle:
Modules:
Lecture: Molecular Biotechnology 2
Semester:
2nd Semester, Summer Semester
Responsible lecturer:
Prof. Dr. Rita Bernhardt
Lecturer:
Prof. Dr. Rita Bernhardt
Language:
German
Level of the unit/
Mandatory or not :
Graduate course / mandatory elective
Course type/weekly
hours:
Total workload:
Lecture: 2 h
Credits:
3
Entrance requirements:
Biochemistry 1 and 2, Molekular Biotechnology 1
Aims/Competences to be
developed:
Knowledge of the methods of the genetic mutation of
productive organisms
Content:
-
Assessment/Exams:
Written exam, protocols
90 h = 30 h of classes and 60 h private study
Characterstics of enzymes
Enzymes in Organic Chemistry
Protein backfolding
Mammalian cells in Biotechnology
Recombinant yeasts in Biotechnology
Techniques of molecular evolution
Examples for SDM in Biotechnology
Examples for directed evolution in Biotechnology
Module Descriptions of the Master Program Bioinformatics, Saarland University
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Program of Studies:
Master Program Bioinformatics
Name of the module:
The Human Genome and its Genetic Diseases
Abbreviation:
B-M-2
Subtitle:
Modules:
Lecture: The Human Genome
Semester:
2nd semester / every summer semester
Responsible lecturer:
Prof. Dr. Eckart Meese
Lecturer:
Prof. Dr. Eckart Meese, Prof. Dr. Cornelius Welter
Language:
German
Level of the unit/
Mandatory or not :
Graduate course / mandatory elective
Course type/weekly
hours:
Total workload:
Lecture: 2 h (weekly)
Credits:
3
Entrance requirements:
Familiarity with the basics of genetics
Aims/Competences to be
developed:
The students will be familiarized with the current level of
research about the human genome. A main focus lies on
mediating the connection between alterations of the human
genome and the occurrence of genetically related diseases.
The students will be enabled to recognize the importance of
polymorphisms and mutations for the occurrence of
genetically related diseases. They will learn to understand the
differences between mutations/ polymorphisms on germ line
level and somatic cell level.
90 h = 32 h of classes and 58 h private study
Module Descriptions of the Master Program Bioinformatics, Saarland University
26
Content:
The lecture mediates basics for understanding mutations in
the human genome. Different kinds of mutations are
presented, the probabilityof mutations for different cell types
are treated, and the verification methods for mutations are
made a subject of discussion. Building on these basics,
different genetically related diseases are presented. The main
focus at this is the connection between certain genetical
alterations and the occurrence or the characteristics of certain
diseases, respecively. Regarding the diseases, the
development of human tumors is lifted besides other topics
Assessment/Exams:
Written or oral exam at teh end of the summersemester, reexam at the beginning of the winter
When participating in both exams, the grade of the last exam
is listed.
Used media:
Presentation with lap-top (power-point).
Literature:
Molekulare Genetik von Knippers
Buselmaier: Humangenetik
Taschenatlas zur Genetik, Passarge
Genetics in Medicine, Thomson
Module Descriptions of the Master Program Bioinformatics, Saarland University
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Program of Studies:
Master Program Bioinformatics
Name of the module:
Abbreviation:
Systems and Synthetic Biology
(former: Functional Genomics and Metabolic Engineering)
B-M-4
Subtitle:
-
Modules:
Lecture, tutorial, and seminar
Semester:
Once every two years
Responsible lecturer:
Prof. Dr. Elmar Heinzle
Lecturer:
Prof. Dr. Elmar Heinzle, Dr. Fozia Noor
Language:
English
Level of the unit/
Mandatory or not :
Graduate course / mandatory elective
Course type/weekly
hours:
Lecture: 2 h (weekly)
Tutorial: 1 h (weekly)
Seminar: 1 h (weekly)
180 h = 60 h of classes and 120 h private study and
assignments
6
Total workload:
Credits:
Entrance requirements:
Aims/Competences to be
developed:
Familiarity with the contents of Organic Chemistry and
Biochemistry, Molecular Microbiology, Biotechnology, and
Bioinformatics 3.
The students get familiar with modern concepts of metabolic
engineering. They should learn to integrate knowledge from
different fields as biochemistry, microbiology, biological
process engineering, bioanalytics, and bioinformatics and to
appliy on biological questions..
The students get familiar with modern concepts of metabolic
engineering. They should learn to integrate knowledge from
different fields as biochemistry, microbiology, biological
process engineering, bioanalytics, and bioinformatics and to
appliy on biological questions..
First of all an essential aim is the comprehension of function
and interaction of the different elements of metabolic and
regulatory networks. A wide part is dedicated to the reaction
networks, whereby the stoichiometric balancing and metabolic
control analysis are emphazised. The students learn to create
and analyse networks for specific biological questions based
on data available in the internet, e.g. by elemantary modes.
They learn by these methods to determine metabolic flux and
Module Descriptions of the Master Program Bioinformatics, Saarland University
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get knowledge of pursuing techniques with the use of stable
isotopes. Biological questions are the production of interesting
metabolites, but also the effects of medicinal drugs, e.g.
encyme inhibitors on the behavior of the corresponding
metabolic network..
The possibilities of the targeted genetic manipulation of
production organisms are discussed. The students should
learn how special analytic methods, particularly of the
expression, metabolom, and proteom analysis can be used
targeted. Computer practicals are an important part, where the
students can base on methods learned in bioinformatics 3.
Content:
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
Introduction to Systems and Synthetic Biology
Metabolic networks
Regulatory networks
Reaction networks – network models and -design
Analysis – genome, transcriptome, proteome,
metabolome
Quantitative proteome analysis
Metabolome analysis
Metabolic flux analysis (fluxome)
Genetic engineering
Modeling of metabolic networks / Metabolic control
analysis
Production of primary metabolites
Production of secondary metabolites
Protein production
Pharmaceutical systems biology
Exercises: description and calculation of metabolic networks,
e.g. elementary modes, metabolic
flux analysis
Seminar : Lecture on recent publication in systems and
synthetic biology
Assessment/Exams:
One written exam, protocols of exercises, seminar talk and
seminar report
Used media:
Power-point lecture.
Internet data bases like e.g. KEGG, programs of elementary
modes analysis, BerkeleyMadonna for dynamic studies and
MATLAB for the metabloic flux analysis.
Literature:
Stephanopoulos et al., Metabolic Engineering,
1999. Solution of exercises
Module Descriptions of the Master Program Bioinformatics, Saarland University
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Program of Studies:
Master Program Bioinformatics
Name of the module:
Bio-Reaction Engineering
Abbreviation:
B-M-5
Subtitle:
-
Modules:
Lecture, tutorial, and seminar
Semester:
1st – 3rd semester / every winter semester
Responsible lecturer:
Prof. Dr. Elmar Heinzle
Lecturer:
Prof. Dr. Elmar Heinzle
Language:
English
Level of the unit/
Mandatory or not :
Graduate course / mandatory elective
Course type/weekly
hours:
Credits:
Lecture: 2 h (weekly)
Tutorial: 1 h (weekly)
Seminar: 1 h (weekly)
180 h = 60 h of classes and 120 h private study and
assignments
6
Entrance requirements:
Basic knowledge mathematics, biochemistry
Aims/Competences to be
developed:
Comprehension of the basics of bio-reaction engineering
(kinetics, drug transport, bio-reactors). This course teaches
the quantitative basis for the description of biochemical and
cellular processes as well as the description of bio-reactors
within a lecture (2 h weekly) with integrated tutorials and a
seminar thesis about a selected topic based on a publication.
Total workload:
Module Descriptions of the Master Program Bioinformatics, Saarland University
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Content:
1.
2.
3.
4.
5.
6.
7.
8.
9.
Thermodynamics of biological processes
Mass and energy balances
Enzyme kinetics
Growth kinetics
Kinetics of cellular processes
Metabolic balances
Material transport
Bioreactors GL
Interpretation of bioreactors (enzymes, bacteria, fungi,
cell cultures)
10. Recycling systems (membrane processes, perfusion)
11. Integrated separation of products
12. Diffusion and reaction
13. Immobilized biocatalysts
14. Online measurement and control- 3 rd
Assessment/Exams:
Exam, assignments
Literature:
Dunn, Heinzle, Ingham, Prenosil. Biological Reaction
Engineering, 2003
Module Descriptions of the Master Program Bioinformatics, Saarland University
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Program of Studies:
Master Program Bioinformatics
Name of the module:
Abbreviation:
Special-topic Lecture Biosciences:
Virology and Immunology
B-M-6
Modules:
Lecture
Semester:
1st – 3rd semester / every winter semester
Responsible lecturer:
Prof. Dr. Hagen von Briesen
Lecturer:
Prof. Dr. Hagen von Briesen
Language:
English
Level of the unit/
Mandatory or not :
Graduate course / mandatory elective
Course type/weekly
hours:
Lecture: 2 h (weekly)
Total workload:
90 h = 30 h of classes and 60 h private study
Credits:
3
Entrance requirements:
Basic knowledge in molecular biology
Aims/Competences to be
developed:
Advanced knowledge in Virology and Viral Immunology
Content:
-
Assessment/Exams:
Written exam
Methods:
Lecture, film presentations, written tests, excursion
to the “HIV Specimen Cryorepository”
Virus Classification and Taxonomy
Virus Replication
Virus Variation
Diagnostics
Viral Pathogenesis
Hepatitis Viruses (HBV, HCV)
Human Immunodeficiency Virus (HIV-1)
Influenza Virus
Antiviral Treatment
Vaccination
Prions
Module Descriptions of the Master Program Bioinformatics, Saarland University
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Program of Studies:
Master Program Bioinformatics
Name of the module:
Abbreviation:
Special-topic Lecture Biosciences: Advances in Drug
Delivery: Vaccination
B-M-6
Modules:
Advances in Drug Delivery: Prospects for Vaccination
Semester:
1st-4th semester, every summer term
Responsible lecturer:
Dr. Eva Collnot
Lecturer:
Language:
Dr. Eva Collnot, Dr. Steffi Hansen, Dr. Nicole Daum, Dr. Brigitta
Loretz
English
Level of the unit/
Mandatory or not
Graduate course / mandatory elective - Advanced Lectures of
Life Sciences
Course type/weekly
hours:
Lecture and seminar: 2h (weekly)
Total workload:
90 h = 30 h in class and 60 h private study and assignments
Credits:
3
Entrance requirements:
Bachelor degree in science.
Aims/Competences to be
developed:
The students
- define the terms ‘immunology, immunity, immune system,
immune tolerance’
- name cells, tissues and organs of the immune system
- describe components and functional principals of adaptive
and innate immunity
- compare unspecific inflammation and adaptive immune
response concerning their sequence of events and
consequences
- compare the mechanisms of action of different types of
vaccines and adjuvants
- identify issues in drug delivery of vaccines and adjuvants
- name and describe strategies to overcome these issues
- describe preparation methods for nano- and micro-scaled
drug carriers
- describe preparation methods for liquid dosage forms
- name regulatory requirements for liquid dosage forms
- define differences between solutions, colloidal solutions,
suspensions, emulsions and name their characteristics
important for drug delivery
- theoretically develop a vaccine formulation in the course of
consecutive homework assignements
Module Descriptions of the Master Program Bioinformatics, Saarland University
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Content:
-
viral and bacterial infections
immune tolerance vs. autoimmunity
vaccination (dosing schemes, immune priming, active vs.
passive immunization)
vaccines (inactivated and attenuated vaccines, sub unit
vaccines, DNA vaccines, synthetic vaccines)
adjuvants (aluminum salts, virus-like particles, nanoparticles,
new adjuvants in the development pipelines)
drug delivery (macroscopic formulations, particle technology,
drug delivery issues of vaccines)
regulatory requirements (pharmacopoeia) for liquid and sterile
dosage forms
routes of application (parenteral, oral, mucosal – nasal,
vaginal, sublingual, subcutaneous, intradermal)
Assessment/Exams:
Graded: yes
Successful presentation of a research paper (1/3) and a final
written exam (2/3 of total grade).
Used Media:
key-note speech, panel discussion, presentations, work in small
groups
Literature:
Garland Science - Janeway's Immunobiology
Lehrbuch der Pharmazeutischen Technologie - Bauer / Frömming
/ Führer
Pharmazeutische Technologie – Rudolph Voigt
Martin’s Physical Pharmacy
Module Descriptions of the Master Program Bioinformatics, Saarland University
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Program of Studies:
Master Program Bioinformatics
Name of the module:
Special-topic Lecture Biosciences: Bioanalytics
Abbreviation:
B-M-6
Subtitle:
-
Modules:
Lecture and tutorial „Bioanalytics“
Semester:
1st – 3rd semester
Angebotsturnus:
Responsible lecturer:
Prof. Dr. Dietrich Volmer
Lecturer:
Prof. Dr. Dietrich Volmer, PD Dr. Ralf Kautenburger
Language:
German
Level of the unit/
Mandatory or not :
Graduate course / mandatory elective
Course type/weekly
hours:
Lecture: 2 h (weekly)
Tutorial: 1 h (weekly)
Total workload:
150 h = 48 h of classes and 102 h private study
Credits:
5
Entrance requirements:
Basics of instrumental analytics
Basics of organic chemistry and biochemistry
Aims/Competences to be
developed:
Comprehension of the characteristics of biological molecules
in regard to the applicability of different methods to their
separation, Isolation, and information about their structure.
Specifics of biological macromolecules at the separation and
structural analysis.
Module Descriptions of the Master Program Bioinformatics, Saarland University
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Content:
Assessment/Exams:
- Physical-chemical characteristics of biomolecules, their
applicability at their separation by different separating
mechanisms (chromatography, electrophoresis) and
structural analysis (wet chemical Methods, nuclear
magnetic resonance, mass spectrometry).
- Protein analytics: chromatographic and electrophoretic
separation and analysis, peptide-mapping, detection of
post-translatorical modifications, ESI-mass
spectrometry and MALDI-mass spectrometry of
peptides and proteins, protein sequence analysis, 3-Dstructural information of NMR, bioinformatical tools in
proteom analysis, applications in proteom analysis
- Nucleic acid analytics: chromatographical and
elektrophoretical separation and analysis, digestion by
restriction encymes and polamerase-chain reaction,
ESI-mass spectrometrie and MALDI-mass
spectrometrie of nucleioc acids, DANN-sequence
analysis, methods for the detection of mutations,
bioinformatical tools in genome analysis, application in
forensics and medicinical diagnostics
- Carbohydrate analysis: determination of sugar building
blocks, chromatographic and electrophoretical
separation Mass spectrometry, analysis of
polysaccharides and glyco-proteins.
Written exam at the end of the semester
Module Descriptions of the Master Program Bioinformatics, Saarland University
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Program of Studies:
Master Program Bioinformatics
Name of the module:
Special-topic Lecture Biosciences: Biophysical Chemistry
Abbreviation:
B-M-6
Modules:
Lecture and tutorial „Biophysical Chemistry“
Semester:
1st – 3rd semester, once in a year
Responsible lecturer:
Prof. Dr. Gregor Jung
Lecturer:
Prof. Dr. Gregor Jung
Language:
German
Level of the unit/
Mandatory or not :
Graduate course / mandatory elective
Course type/weekly
hours:
Total workload:
Lecture: 2 h
Tutorial: 1 h (compulsory attendance)
150 h = 45 h of classes and105 h private study
Credits:
5
Entrance requirements:
Physics and physical chemistry, basic knowledge of dynamics,
kinetics, spectroscopy and optics are strongly recommended
Aims/Competences to be
developed:
Technical basics of biophysical chemistry with main focus on
microscopical and spectroscopical methods. The students
should learn which method leads to resolve a certain problem
and get an overview in current trends in biophysical chemistry.
The lecture is regarded as supplement to the lectures
Biophysics (Prof. Dr. I. Bernhardt) and Bioanalytics (Prof. Dr.
D. Volmer).
Module Descriptions of the Master Program Bioinformatics, Saarland University
37
Content:
The lecture treats techniques of biophysical chemistry that are
neither presented in the lecture and practical „Bioanalytcs“ nor
in „Biophysics 1 and 2“.
1. Spectroscopy and its flection with electromagnetic radiation
1.0 Principles of the interaction „light-matter“: time-dependend
perturbation theory, Einstein coefficients, sensitivities
1.1 Magnetic resonance spectroscopy: comparison
ESR/NMR; anisotropy of the chemical displacement,
dipole-dipole interaction (static, energy splitting)
1.2 Element selectivity: X-ray and Mößbauer spectroscopy:
Fe-Mößbauer, nuclear quadrupole moment, EXAFS
1.3 Functional groups I: IR and Raman spectroscopy:
selection rules, resonance Raman effect
1.4 Electronic incitations: techniques of UV-ViS and
fluorescence spectroscopy (static): protein absorption,
chiroptic techniques, determination of heterogeneities via
hole burning & single molecule spectroscopy,
Fluorescence Activated Cell Sorting, anisotropy
2. Solving of dynamics and kinetics
2.0 Principles: time scales: diffusion controlled and
unimolecular reactions, transition state, Fourier
transformation
2.1 Non-equilibrium dynamic: time-resolved spectroscopy and
crystallography (fs – ms), caged compounds, NMR:
relaxation of magnetization (T1, T2), linie breadths
2.2 Equilibrium fluctuations: coalescence, Fluorescence
Correlation Spectroscopy (FCS)
2.3 Energy transfer and two-dimensional spectroscopy: dipoledipole interaction (dynamic), energy transfer (FRET),
NOESY
3. Image processing (microscopy, tomography)
3.0 Principles: resolution capability and in-vivo suitability:
criteria of resolution capability, optic coherence
tomography, optic window im NIR
3.1 Contrast mechanisms: spectroscopic contrast via
nonlinear optic procedures
3.2 Fluorescence microscopy: confocal and TIRF microscopy,
fluorescence in situ hybridisation (FiSH), two-photon
microscopy, STED microscopy, dynamic microscopy (FRAP,
photoactivation)
Assessment/Exams:
Oral exam
Used media:
Board, powerpoint lecture, etc. (can be downloaded with more
information from the webpage).
Literature:
Physikalische Chemie: P. Atkins
Biophysikalische Chemie: R. Winter, F. Noll:
Methoden der Biophysik. Chemie, Teubner 1998
K. van Holde, W.C. Johnson, P.S. Ho: Principles of
Physical Biochemistry, 2nd Ed. Person Educ. 2006
Module Descriptions of the Master Program Bioinformatics, Saarland University
38
Program of Studies:
Master Program Bioinformatics
Name of the module:
Special-topic Lecture Biosciences: Cellular Programs
Abbreviation:
B-M-6
Modules:
Lecture and tutorial „Cellular Programs“
Semester:
1st – 3rd semester, every summer semester
Responsible lecturer:
Prof. Dr. Volkhard Helms
Lecturer:
Prof. Dr. Volkhard Helms
Language:
English
Level of the unit/
Mandatory or not :
Graduate course / mandatory elective
Course type/weekly
hours:
Total workload:
Lecture: 2 h
Tutorial: 1 h
150 h = 45 h of classes and105 h private study
Credits:
5
Entrance requirements:
Basic knoelegde in genetics and molecular biology
Aims/Competences to be
developed:
The lecture will cover various topics in current cell biology. The
students will be forced to work actively throughout the whole
semester. Each lecture will introduce a new topic and students
will be given one paper from the current original literature on this
topic. The assignment sheet will consist of questions about this
paper. Answers have to be submitted electronically. Assignments
will be corrected and the solutions will be discussed in the tutorial.
One group of 2-3 volunteer students will present the main
scientific findings of the paper at the beginning of the next lecture.
Each student has to present at least once during the semester.
The presentations will not be graded.
This course will enter into details of four topics in cellular
programs:
* (I) cell cycle
* (II) circadian clocks
* (III) apoptosis (cell death)
* (IV) reprogramming of pluripotent cells
At least 50% of points from the 10 weekly assignments, one
paper presentation, and passing of three short tests out of four.
The grade is then computed as the average of the three short
tests.
Papers to be distributed in the lecture.
Content:
Assessment/Exams:
Literature:
Module Descriptions of the Master Program Bioinformatics, Saarland University
39
Program of Studies:
Master Program Bioinformatics
Name of the module:
Abbreviation:
Special-topic Lecture Biosciences: Mechanisms of
epigenetic gene regulation
B-M-6
Modules:
Lecture
Semester:
1st – 3rd, each summer semester
Responsible lecturer:
Prof. Dr. Jörn Walter
Lecturer:
Prof. Dr. Jörn Walter, PD Dr. Martina Paulsen
Language:
English
Level of the unit/
Mandatory or not :
Graduate course / mandatory elective
Course type/weekly
hours:
Total workload:
Block lecture, 3 weeks (2 SWS)
Credits:
3
Entrance requirements:
Open for all participants with good knowledge in molecular
genetics
The lectures introduce into epigenetic principles and concepts
providing examples of biological effects of epigenetic regulation in
diverse organisms with a strong focus of its biomedical relevance
for human health and disease.
Aims/Competences to be
developed:
Content:
Assessment/Exams:
Literature:
90 h = 30 h of classes and 60 h private study
1. Introduction, Chromatin
2. Chromatin II
3. Enzymetic control of DNA-methylation
4. Epigenomics and functional genome analysis
5. Genome imprinting 1
6. Gene regulation by small RNAs
7. Genome imprinting 2
8. Epigenetics and complex diseases: Cancer 1
9. Epigenetics and complex diseases: Cancer 2
10. Epigenetic model systems
11. Sex determination and dosis compensation
12. Epigenetic reprogramming
13. Summary
Written exam
C. David Allis, Thomas Jenuwein, Danny Reinberg, Marie-Laure
Caparros: Epigenetics, CSHL Press 2007
Module Descriptions of the Master Program Bioinformatics, Saarland University
40
Program of Studies:
Master Program Bioinformatics
Name of the module:
Special-topic Lecture Biosciences: Medical Biotechnology
Abbreviation:
B-M-6
Modules:
Lecture
Semester:
1st – 3rd, each summer semester
Responsible lecturer:
Prof. Dr. Heiko Zimmermann
Lecturer:
Prof. Dr. Heiko Zimmermann, Prof. Dr. Günter Fuhr
Language:
German
Level of the unit/
Mandatory or not:
Graduate course / mandatory elective
Course type/weekly
hours:
Total workload:
Lecture: 2 h
Credits:
3
Entrance requirements:
Basic knowledge biochemistry and biology
Aims/Competences to be
developed:
Advance knowledge biochemistry and biology
Content:
Assessment/exams:
90 h = 30 h of classes and 60 h private study
1.
2.
3.
4.
5.
6.
7.
8.
Biocompatibility I: Basics
Biocompatibility II: Implants
Nanobiotechnology I
Nanobiotechnology II
Electric manipulation of cells
Immobilization and encapsulation
Cryobiotechnology I: Biophysical and cell biological basics
Cryobiotechnology II: Life in low temperatures: Algae,
bacteria, plants)
9. Cryobiotechnology III: Cryo conservation and cryo banking
(stem cell data bases, reproductive medicine)
10. Cryobiotechnology IV: Medical application and outlook
(tissue banking)
11. Cell therapies I: Overview
12. Cell therapies II: Immune isolated transplantation
13. Cell therapies III: Stem cell therapy
14. Cell therapy IV: Regenerative medicine and outlook
Written exam
Module Descriptions of the Master Program Bioinformatics, Saarland University
41
Program of Studies:
Master Program Bioinformatics
Name of the module:
Special-topic Lecture Biosciences: Systems Toxicology
Abbreviation:
B-M-6
Modules:
Lecture
Semester:
1st – 3rd, winter semester
Responsible lecturer:
Dr. Fozia Noor
Lecturer:
Dr. Fozia Noor
Language:
English
Level of the unit/
Mandatory or not :
Graduate course / mandatory elective
Course type/weekly
hours:
Total workload:
Lecture and seminar, 2 SWS
Credits:
3
Entrance requirements:
Basic knowledge in biochemistry, cell biology, systems biology
and instrumental analytics
Aims/Competences to be
developed:
Understanding complex “omics” data and the application of
Systems Biology approach to toxicology and
human health
Content:
-
90 h = 30 h of classes and 60 h private study
-
-
-
Assessment/Exams:
Use and interpretation of genomics and epigenomics data in
a systems approach, genetic and genomic approaches to
the identification of toxic effects, integrative analysis of
microarray data, applications in systems toxicology
Proteomics, metabolomics and fluxomics: their meaning in
global understanding of systems and application in drug
discovery and development, application for the study of
mechanisms of toxicity
In vitro alternatives to animal testing in toxicology, body on
a chip, challenges
Systems toxicology modeling, multi scale integration of
system organization, in silico tools for modeling, Systems
toxicology modeling for prediction in humans
Application to predictive, preventive and personalized
medicine, new paradigm based on systems approach to
diagnostics and treatment, advances in drug discovery
/biomarker discovery and drug development
Written exam
Module Descriptions of the Master Program Bioinformatics, Saarland University
42
Module: Advanced Lecture of Bioinformatics
Program of Studies:
Master Program Bioinformatics
Name of the module:
Bioinformatics 3
Abbreviation:
BI-M-1
Subtitle:
-
Modules:
Lecture and tutorial Bioinformatics 3
Semester:
1st semester / every winter semester
Responsible lecturer:
Prof. Dr. Volkhard Helms
Lecturer:
Prof. Dr. Volkhard Helms, Dr. Tihamér Geyer
Language:
English
Level of the unit/
Mandatory or not :
Graduate course / mandatory elective
Course type/weekly
hours:
Total workload:
Lecture: 4 h (weekly)
Tutorial: 2 h (weekly)
270 h = 90 h of classes and 180 h private study and
assignments
9
Credits:
Entrance requirements:
Familiarity with contents of Bioinformatik I and II. The students
will have to complete programming assignments with Python.
Aims/Competences to be
developed:
The students will get familiar with modern concepts for the
integrated analysis and representation of cellular proteomic
data. An ambitious element of this advanced lecture is to
integrate knowledge of different fields of bioinformatics. The
development of algorithmic techniques for the treatment of
networks on the one hand and the representation of the
application in current biological works are especially
significant. The assignments are very important to support the
lecture.
Parts of the assignments are programming assignments,
where the students implement and apply algorithms and
statistical methods on biological data. At this they learn
with assistance or independently important programming
techniques for a later self-contained research. The result
should be reasonably interpreted
Other assignments contain mathematical derivations or
algorithmic processing"
Module Descriptions of the Master Program Bioinformatics, Saarland University
43
Content:
The course will cover methodological aspects of integrated
biology and systems biology:
- protein-protein interaction networks (mathematical graphs,
Bayesian networks)
- analysis of protein complexes (density fitting, Fourier
transformation)
- transcriptional regulatory networks (Boolean networks)
- dynamic simulation of cellular processes (differential
equation solvers, stochastic simulations)
- metabolic networks (linear algebra)
- and modern applications in synthetic biology
Assessment/Exams:
There will be four 45-minutes tests on different parts of the
lecture. An averaged score will be computed from the best
three results of the four tests. This score will count 50% for the
grade of certification ("Schein"). The other 50% are taken from
the mark in the final exam (120 min) that will (mostly) cover
the material of the assignments.
Condition for the participation in the final exam: (a) successful
participation in 3 out of the 4 tests, (b) at least half of the
points of the assignments. Solutions have to be returned at
the beginning of the following Friday´s lecture. In addition
each student has to solve one of these problems on the
blackboard.
Used media:
Powerpoint presentation
Literature:
V. Helms, Principles of Computational Cell Biology, Wiley
(2008)
Module Descriptions of the Master Program Bioinformatics, Saarland University
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Program of Studies:
Masterstudiengang Bioinformatik
Name of the module:
Special-topic Lecture Bioinformatics: Acquisition,
Analysis & Management of Biological Image Data
Abbreviation:
BI-BM-1
Modules:
Lecture and tutorial: Acquisition, Analysis & Management of
Biological Image Data
Semester:
2nd semester master / summer semester
Responsible lecturer:
Dr. Oliver Müller
Lecturer:
Dr. Oliver Müller
Language:
English
Level of the unit/
Mandatory or not :
Graduate course / mandatory elective
Course type/weekly
hours:
Total workload:
Lecture: 2 h (weekly)
Tutorial: 1 h (weekly)
150 h = 48 h of classes and 102 h private study
Credits:
5
Entrance requirements:
The course is targeted to advanced bachelor students (6th
semester with knowledge in basic and advanced practical
courses in life sciences) and master students in
bioinformatics.
Aims/Competences to be
developed:
The goal of this special lecture is to discuss the different
aspects of biological image data from image acquisition,
processing & analysis techniques to data storage and
archiving methods used in life sciences. It elucidates the entire
workflow “from image data to results”. Finally, the course
should prepare students for master and Ph.D. theses at the
interface between bioinformatics and life sciences research.
Content:
•
•
•
•
Data acquisition (imaging techniques and imaging
systems)
Data analysis (algorithms and approaches)
Data storage and archiving (strategies)
Experimental workflow „from image data to results“
Module Descriptions of the Master Program Bioinformatics, Saarland University
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Assessment/Exams:
About 10 assignments in groups of two students.
Participation in the written exam if at least 50 % of all scores
are achieved.
Second chance written exam at the beginning of the following
semester.
Used media:
Power point presentation combined with presentations at the
blackboard.
Literature:
Special literature that can be downloaded from the webpage
of the lecture.
Module Descriptions of the Master Program Bioinformatics, Saarland University
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Program of Studies:
Master Program Bioinformatics
Name of the module:
Special-topic Lecture Bioinformatics:
Discrete Computational Biology
Abbreviation:
BI-BM-1
Modules:
Lecture and tutorial: Discrete Computational Biology
Semester:
1nd - 3rd semester master / winter semester
Responsible lecturer:
Dr. Marc Hellmuth
Lecturer:
Dr. Marc Hellmuth
Language:
English
Level of the unit/
Mandatory or not
Graduate course / mandatory elective
Course type/weekly
hours:
Lecture: 2h (weekly)
Tutorial: 1h (weekly)
Total workload:
150 h = 48 h of classes and 102 h private study
Credits:
5
Entrance requirements:
Familiarity with discrete mathematics, bioinformatics 1 and 2,
basics of programming, and algorithms.
Starting with an introduction into basic discrete mathematics, in
particular graphtheory, we will turn on to explore their application
in biology.
Specially, we are concerned with RNA (e.g. folding,
combinatorical problems), with the reconstruction of gene- and
species trees, with graph products and phenotypespaces.
The special lecture should prepare students for master and Ph.D.
theses at the interface between biological problems,
bioinformatics and discrete mathematics.
- Basics of discrete mathematics
- RNA
- Reconciliation Trees
- Phenotypespaces
- Other problems
About 7 exercises.
Participation in the written exam if at least 50 % of all scores of
exercises are achieved.
Second chance to write exam.
Power point presentation combined with presentations at the
blackboard.
Special literature that can be downloaded from the webpage of
the lecture.
Aims/Competences to be
developed:
Content:
Assessment/Exams:
Used Media:
Literature:
Module Descriptions of the Master Program Bioinformatics, Saarland University
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Program of Studies:
Master Program Bioinformatics
Name of the module:
Special Lecture Bioinformatics: Statistical Learning 1
Abbreviation:
BI-BM-1
Subtitle:
-
Modules:
Semester:
Lecture: Statistical Learning 1
Turorial: Statistical Learning 1
1st semester master / every summer semester
Responsible lecturer:
Prof. Dr. Thomas Lengauer, Ph.D.
Lecturer:
Prof. Dr. Thomas Lengauer, Ph.D.
Language:
English
Level of the unit/
Mandatory or not :
Graduate course / mandatory elective
Course type/weekly
hours:
Total workload:
Credits:
Lecture: 2 h (weekly)
Tutorial: 1 h (two hours every other week)
150 h = 48 h of classes and 102 h private study and
assignments
5
Entrance requirements:
Basics of statistics and development of algorithms
Aims/Competences to be
developed:
This course covers a subject that is relevant for computer
scientists in general as well as for other scientists involved in
data analysis and modelling. It is not limited to the field of
computational biology.
The course will be the first part of a two semester course on
Statistical Learning. The first part (SS 2011) will concentrate
on chapters 1-5 and 7-10 of the book
The Elements of Statistical Learning, Springer, second edition
2099)
Module Descriptions of the Master Program Bioinformatics, Saarland University
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Content:
(1) Introduction to statistical learning
(2) Overview over Supervised Learning
(3) Linear Regression
(4) Linear Classifikation
(5) Splines
(6) Model election and estimation of the test errors
(7) Maximum-Likelihood Methods
(8) Additive Models
(9) Decision trees
(10) Boosting
Assessment/Exams:
You need a cumulative 50% of the points in the problem sets
to be admitted to the oral exam. A score of 50% in the exam is
then considered a passing grade.
Used media:
Power point presentation
Literature:
Lecture slides, tutorial handouts and problem sets are
available in the password protected area.
„The Elements of Statistical Learning“ von Hastie, Tibshirani
und Friedman, chapters 1,2,3,4,5,7,8,9,10.
Familiarize yourself with the R programming language. You
might find the following tutorials useful:
- R for Beginners by Emmanuel Paradis. Especially relevant
for us are chapters 1, 2, 3 and 6.
- An Introduction to R - the standard R introduction. This is a
very detailed manual; it is therefore quite lengthy.
Module Descriptions of the Master Program Bioinformatics, Saarland University
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Program of Studies:
Master Program Bioinformatics
Name of the module:
Special Lecture Bioinformatics: Statistical Learning 2
Abbreviation:
BI-BM-1
Subtitle:
-
Modules:
Semester:
Lecture: Statistical Learning 2
Turorial: Statistical Learning 2
2nd Semester Master/ every summer semester
Responsible lecturer:
Dr. Thomas Lengauer, PhD
Lecturer:
Dr. Thomas Lengauer, PhD
Language:
English
Level of the unit/
Mandatory or not :
Graduate course / mandatory elective
Course type/weekly
hours:
Lecture: 2 h (weekly)
Tutorial: 1 h (two hours every other week)
Total workload:
150 h = 48 h of classes and 102 h private study and
assignments
Credits:
5
Entrance requirements:
The course is targeted to advanced students in math,
computer science and general science with mathematical
background. Students should know linear algebra and have
basic knowledge of statistics. Attendance of Statistical
Learning I is recommended, however not required if a student
has basic knowledge in machine learning
Aims/Competences to be
developed:
The course is the second part of a two semester course on
Statistical Learning. The first part (SS 2011) concentrated on
chapters 1–5 and 7-10 of the book „The Elements of Statistical
Learning“, Springer 2009. The second part will present the
remaining bookchapters, focusing on advanced topics in
supervised and unsupervised leaning, such as kernel
methods, SVMs, neural networks, random forests and
clustering. The theoretical models will be illustrated with
interesting applications, out of which many are challenging
problems in the field of bioinformatics.
This course covers a subject that is relevant for computer
scientists in general as well as for other scientists involved in
data analysis and modeling. It is not limited to the field of
computational biology.
Module Descriptions of the Master Program Bioinformatics, Saarland University
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Content:
Tentative course and tutorial schedule
- Repetition - Overview - Outlook
- Neural Networks (HTF chapter 11)
- Support Vector Machines (HTF chapter 12)
- Prototype Methods and Nearest-Neighbors (HTF
chapter 13)
- Unsupervised Learning I (HTF chapter 14)
- Unsupervised Learning II (HTF chapter 14)
- Kernel Methods (HTF chapter 6)
- Normalization of Gene Expression Data
- Classification of Gene Expression Data
- Statistical Analysis with the Gene Ontology
- Classification of Protein Structures
- Learning with Mixtures of Trees
- Analysis of ArrayCGH Data
Assessment/Exams:
You need a cumulative 50% of the points in the problem sets
to be admitted to the oral exam. A score of 50% in the exam is
then considered a passing grade.
Used media:
Powerpoint presentation
Literature:
Hastie, Tibshirani, Friedman: The Elements of Statistical
Learning, Springer 2009. The readers of the course are
encouraged to acquire this book. You can download it as a
PDF file from the dedicated page on Charlie Tibshirani's web
site. More information on this book, as well as a contents
listing can be found on the Springer web site.
Module Descriptions of the Master Program Bioinformatics, Saarland University
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Program of Studies:
Master Program Bioinformatics
Name of the module:
Special Lecture Bioinformatics: Next Generation
Sequencing
BI-BM-1
Abbreviation:
Subtitle:
Modules:
Lecture and Turorial: Next Generation Sequencing
Semester:
Responsible lecturer:
Yearly during the winter term as a block course of 10 days
after the lecture period
Dr. Barbara Hutter
Lecturer:
Dr. Barbara Hutter, Lars Feuerbach
Language:
English
Level of the unit/
Mandatory or not :
Graduate course / mandatory elective
Course type/weekly
hours:
Total workload:
Lecture: 2 h
Tutorial: 1 h
150 h = 48 h of classes and 102 h private study
Credits:
5
Entrance requirements:
Recommended are the lectures Bioinformatics 1 and 2,
Softwarewerkzeuge der Bioinformatik; basic knowledge of
Biology,Genetics, and Biostatistics; proficiency in applying
Unix command line
Aims/Competences to be
developed:
The lecture gives an introduction into modern bioinformatic
methods for analyzing high throughput ("Next Generation")
sequencing data. It is aimed at advanced students of
Bioinformatics (master program) who intend processing such
data in their master thesis and/or future working field. The
students will get familiar with the basics of modern high
throughput sequencing as well as the mathematical and
algorithmic background of existing analysis programs. Using
examples from up-to-date (tumor) genome research, typical
problems and solution approaches will be presented. For
deepening understanding of the lecture contents, there will be
theoretical and practical exercises. The students will acquire
the necessary knowledge and skills to allow independent
research and communication with experimental working
groups in the currently fast expanding field of high throughput
sequencing.
Module Descriptions of the Master Program Bioinformatics, Saarland University
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Content:
1. Introduction
What is Next Generation Sequencing, which biological
questions are approached with it, which are the
bioinformatic challenges?
2. Platforms
How does sequencing work, which output formats exists,
how much data is produced?
3. Alignment
Why not BLAST? Alternatives: Borrows-Wheeler
Transformation, binary alignment format
4. Whole genome Sequencing
1000 Genomes Project, Sequencing of tumor genomes
5. Point mutations
Finding point mutations and comparison with normal
genome (of the same patient) = discern natural variations
from disease-associated ones
6. Annotation
Effect of mutations in coding exons (conservation MSA,
protein structure), noncoding: transcription factor binding
sites
7. Indels
Effects of small insertions and deletions in coding exons,
noncoding regions
8. Amplifications, Deletions, Rearrangements
Overexpression by multiple copies (e.g. MYC), activating
and inactivating gene fusions, loss of heterozygosity
9. Assembly
New challenges by short sequences
10. Epigenome
Defects in epigenetic machinery and their effects on gene
expression etc.
11. ChIP-seq
DNA binding proteins and histone modifications
12. RNA-Seq
Expression profiles; is the mutated allele expressed at all?
Detection of gene fusions on RNA level
13. Special applications
miRNA-Seq and PAR-ClIP, viral elements
14. 3rd generation sequencing
Assessment/Exams:
Autonomous processing of about 7 examination sheets that
are partially handed out as homework, partially to be solved in
practical tutorials.
Admission to the final exam: at least 50% of points from the
homework achieved. After failure to pass the final exam there
is the possibility to pass an oral exam.
This course is marked: yes
The mark confers to the mark of the final exam.
The lecture will be presented predominately using electronic
slides. Some excercises require access to internet and
publically available online databases and software.
Used media:
Module Descriptions of the Master Program Bioinformatics, Saarland University
53
Literature:
So far, no textbook covers the topics of this course. Instead,
the electronic slides of the lectures will be made available on
the web side of the course The original publications quoted
therein are recommended for further self studies.
Module Descriptions of the Master Program Bioinformatics, Saarland University
54
Program of Studies:
Master Program Bioinformatics
Name of the module:
Abbreviation:
Special Lecture Bioinformatics: Modern Methods in Drug
Discovery
BI-BM-1
Subtitle:
-
Modules:
Semester:
Lecture: 2 h (weekly)
Tutorial: 1 h (2 h every second week)
1.st semester/ yearly during the winter term
Responsible lecturer:
Dr. Michael Hutter
Lecturer:
Dr. Michael Hutter
Language:
English/German
Level of the unit/
Mandatory or not :
Course type/weekly
hours:
Total workload:
Graduate course / mandatory elective
Credits:
Entrance requirements:
Aims/Competences to be
developed:
Lecture: 2 h (weekly(
Tutorial: 1 h (weekly)
150 h = 48 h of classes and 102 h private study and
assignments
5
Recommended are the lectures Bioinformatics 1 and 2,
Computational Chemistry, and
Softwarewerkzeuge der Bioinformatik
Basic knowledge of either Chemistry, Biology, Biochemistry
and Genetics
During the course the students will get familiar with current
methods of bioinformatics and chemoinformatics in the
development of pharmaceutcial drugs and their molecular
targets also on the level of genes. Subsequently, the students
should be able to set their mark within interdisciplinary
research groups.
The combination of knowledge from bioinformatics and the
other natural and life sciences is a demanding aspect of this
course. Focus is the applicability of bioinformatical knowledge
onto the field of pharmaceutcally relevant tasks. The
excercises play an important role in depeening the
understandig:
- about half of the excercises consist of application of
computer programs onto selected biological systems that
act as a model.
- the other half serves the consoldiation and extension of
special knowledge
In total, the emphasis is set on critical evaluation and
interpretation of results in order to allow subsequent
independent research and to strengthen scientific
communication skills.
Module Descriptions of the Master Program Bioinformatics, Saarland University
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Content:
The main point of the course is set on the computer-assisted
prediction of suitable pharmaceutical drugs and the search for
new potential target in the human genome.
Following topics are covered:
(1) molecular causes of typical diseases and mechanism
of action of pharmaceutical drugs
(2) virtual compound libraries and search strategies
(3) in silico eADMET-models and filters, bioavailability
(4) statistics and QSAR-methods
(5) metabolism, toxicology and adverse side effects with
respect to biomarkers
(6) polymorphism und susceptible genes
(7) indentification of orthologue genes for deriving new
targets and model organisms
(8) current trends and strategies
Assessment/Exams:
Autonomous processing of 6 examination sheets that are
handed out biweekly as homework.
Admission to the final exam: at least 50% of points from the
homework achieved. After failure to pass the final exam there
is the possibility to pass an oral exam.
This course is marked: yes
The mark confers to the mark of the final exam.
Used media:
The lecture will be presented predominately using electronic
slides.
Some excercises require access to internet and publically
available online databases.
Literature:
So far, no single textbook covers all the topics of this course.
Instead of, the electronic slides of the lectures will be made
available on the web side of the course
(http://gepard.bioinformatik.uni-saarland.de/teaching/ws-201112/stl-bioinformatics-mmdd-ws1112)
The original publications quoted are recommended for further
self studies. Furthermore, a precompiled set of textbooks is
available in the library.
Module Descriptions of the Master Program Bioinformatics, Saarland University
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Module: Lectures to achieve Key Qualifications
Program of Studies:
Master Program Bioinformatics
Name of the module:
Organisation of Scientific Work
Abbreviation:
E-BM-1
Subtitle:
-
Modules:
Lecture
Semester:
Recommended at the end of the bachelor program
Angebotsturnus:
About every 2nd year
Responsible lecturer:
Stiudents dean
Lecturer:
Prof. Dr. Volkhard Helms
Language:
German
Level of the unit/
Mandatory or not :
Elective course
Course type/weekly
hours:
Total workload:
Lecture: 1 h, three meetings of 4 h each (afternoon)
Credits:
1
Entrance requirements:
-
Aims/Competences to be
developed:
The students should get knowledge of the typical professional
career as a graduate in computational biology and recognize
which personal skills are necessay to reach these targets.
Introduction to ethics of scientific research
30 h = 16 h of classes and 14 h private study
Module Descriptions of the Master Program Bioinformatics, Saarland University
57
Content:
Three topics:
- Types of career in sciences and economy
What means „a scientific career“?
Everyday life in the industry, typical hierarchy,
fellowship systems
- personal qualification
my own personality
networking
staffing
- scientific ethics:
publishing, correct quotation
examples of scientific misbehavior
Assessment/Exams:
A short quiz, no grades
Used media:
Literature:
Kathy Barker At the Helm, Cold Spring Harbor Laboratory
Press
Siegfried Bär, Im Reiche der Propheten, LJ-Verlag (Führer
durch die deutsche Wissenschaftsförderung)
Max-Planck-Gesellschaft: Broschüre "Verantwortliches
Handeln in der Wissenschaft"
Module Descriptions of the Master Program Bioinformatics, Saarland University
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Program of Studies:
Master Porgram Bioinformatics
Name of the module:
Project Management
Abbreviation:
E-BM-2
Modules:
Lecture/Tutorial: 1 h
Semester:
Angebotsturnus:
Once every two years
Responsible lecturer:
Students´ Dean
Lecturer:
N.N.
Language:
German
Level of the unit/
Mandatory or not :
Elective course
Course type/weekly
hours:
Total workload:
Lecture/Tutorial: 1 h, three meetings of 4 h each (afternoon)
Credits:
1
Entrance requirements:
-
Aims/Competences to be
developed:
Die Studierenden lernen im Teil 1:
das Handwerkszeug für erfolgreiches Projektmanagement
- eine wirksame Projektorganisation aufzubauen
- komplexe Projekte ziel- und aufgabengerecht zu
strukturieren und zeiteffizient zu behandeln
- Projekte wirksam zu planen, steuern und zu
überwachen
- relevante betriebliche Daten und Informationen
auszuwählen und zu verarbeiten.
60 h = 16 h of classes and 44 h of private study
- Die Studierenden lernen im Teil 2:
Projektziele zu präzisieren und eine Zielpyramide
aufzubauen
- den Aufwand abzuschätzen und Termine, Kosten und
Kapazitäten zu planen
- mit Risiken und Unsicherheit im Projekt umzugehen
- den Projektfortschritt zu überwachen
- ein zielgruppenadäquates Berichtswesen aufzubauen
- Projekte zu steuern und Steuerungsentscheidungen
herbeizuführen
- den Projektplan im Projektverlauf zu optimieren
Module Descriptions of the Master Program Bioinformatics, Saarland University
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Content:
Teil 1 - Grundlagen
- Einführung in das Projektmanagement
- Ziele, Abläufe und Phasen von Projekten
- Phasenmodelle, Zielfindungen, Umfeldanalyse,
Vertragsgestaltung
- Formen der Aufbauorganisation
- Die Grundlagen der Planung in Projekten
- Projektstrukturpläne
- Ablaufplanung, Terminplanung, Meilensteintechnik
- Projektstatusermittlung
- Terminfortschrittsermittlung
- Meilenstein-Trendanalyse
- Fertigstellungswertanalyse
- Informationstechnologien im Projektmanagement
- Qualitätsphilosophie in Projekten
- Qualitätsmanagement in Projekten
Teil 2 - Controlling im Projekt
- Projekt-Kapazität managen
- Kapazitätsplanung
- Bedarfsermittlung und -berechnung der Einsatzmittel
- Projektfinanzierung und Projektkosten managen
- Kostenplanung
- Kostenkontrolle und -überwachung
- Zahlungsmittelbedarf-Planung und Projekt-Cash-Flow
- Wirtschaftlichkeitsrechnung
- Steuerungsmaßnahmen
- Planabweichungen
- Risikoanalyse und -bewertung
- Berichtswesen
- Grundlagen, Arten
- Änderungsmanagement, Claim Management
-
Assessment/Exams:
Attendance to the lecture
A short quiz, no grades.
Used media:
N.N.
Literature:
N.N.
Module Descriptions of the Master Program Bioinformatics, Saarland University
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Program of Studies:
Master Program Bioinformatics
Name of the module:
Patent Law and Bioethics
Abbreviation:
E-BM-3
Subtitle:
-
Modules:
Lecture: 1 h
Semester:
Every 2nd year in the summer semester
Responsible lecturer:
Students´ Dean
Lecturer:
Axel Koch (Patentverwertungsagentur UdS): Patentrecht;
Pia Scherer-Geiß (ZBI): Bioethik
German
Language:
Level of the unit/
Mandatory or not :
Elective Course
Course type/weekly
hours:
Total workload:
Lecture/Tutorial: 1 h, four or five meetings of 3 h each
(afternoon)
30 h = 16 h of classes and 14 h private study
Credits:
1
Entrance requirements:
none
Aims/Competences to be
developed:
Als Vorbereitung auf eine spätere Tätigkeit in der Wirtschaft
und als Anregung für Firmengründer soll der erste Teil dieser
Veranstaltung die Bioinformatik-Studenten in das Gebiet des
Patentrechts einführen.
In einer praktischen Übung werden Patentrecherchen in den
Patent-Datenbanken Depatisnet und Epoline durchgeführt.
Im zweiten Teil der Veranstaltung sollen bioethische
Problembereiche angesprochen werden, mit denen das
Gebiet Bioinformatik in Berührung steht.
Module Descriptions of the Master Program Bioinformatics, Saarland University
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Content:
Bioethik:
1. Einführung
2. Was ist Bioethik?
1. Grundbegriffe und ethische Theorien
2. Bioethik im Rahmen der Bereichsethiken
3. Historische Aspekte
4. Rechtliche Aspekte und Grundlagen
3. Status menschlicher Embryonen
1. Pränatal- und Präimplantationsdiagnostik
2. Embryonale Stammzellenforschung
4. Gentechnische Reproduktionsmedizin
1. Therapeutisches und reproduktives Klonen
5. Patentierung gentechnischer Veränderungen
1. Patente am Leben
6. Organtransplantation/Transplantationsmedizin
7. Patientenverfügungen/Patientenautonomie
8. Sterbehilfe und Euthanasie
Patentrecht:
1. Einführung
1. Geschichte der gewerblichen Schutzrechte
2. Sinn und Zweck der gewerblichen Schutzrechte
3. Überblick über die verschiedenen Schutzrechtsarten
2. Patentrecht
1. Begriff der Erfindung
2. Berechtigte aus und an der Erfindung
3. Schutzumfang und Dauer des Schutzes
3. Patentanmeldung
1. Der Patenanmelde- und -erteilungsprozess
2. Der Aufbau einer Patentschrift
3. Internationale Patentklassifizierung
4. Patentrecherche
1. Sinn und Zweck der Patentrecherche
2. Quellen für die Patentrecherche
3. Einführung in die wichtigsten kostenlosen OnlinePatentdatenbanken
5. Praktische Rechercheübung
1. Depatisnet
2. Espacenet
Assessment/Exams:
Attendance to the lecture
A short quiz, no grades
Used media:
Powerpoint presentation.
Literature:
-
Module Descriptions of the Master Program Bioinformatics, Saarland University
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Module: Advanced Practical Training of Life Sciences
Program of Studies:
Master Program Bioinformatics
Name of the module:
Advanced Practical Training of Life Sciences
Abbreviation:
PB-M-1
Subtitle:
-
Modules:
Pratical Training
Semester:
e.g. during the semster holidays
Responsible lecturer:
Students´ Dean
Lecturer:
Experimental group leaders of the Center for Bioinformatics or
other experimental research groups
Language:
German
Level of the unit/
Mandatory or not :
Compulsory course
Course type/weekly
hours:
Total workload:
4 weeks full-time
Credits:
240 h = 160 h of classes and 80 h private study and
preparation of the report
8
Entrance requirements:
none
Aims/Competences to be
developed:
As a preparation to the professional life, the students should
get knowledge of the workflow and the working atmosphere in
within an experimental research group.
Content:
The research practical training has an experimental character.
The topic depends on current reseearch projects of the
respective research group.
Assessment/Exams:
Certification of the lecturer that the student has finished the
practical training successfully and has written a report. About
the practical training. No grades.
Used media:
-
Literature:
Depending on the topic.
Module Descriptions of the Master Program Bioinformatics, Saarland University
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Module: Tutor
Program of Studies:
Master Program Bioinformatics
Name of the module:
Tutor
Abbreviation:
Subtitle:
Modules:
Semester:
Every semester
Responsible lecturer:
N.N.
Lecturer:
Qualified students
Language:
German / English
Level of the unit/
Mandatory or not:
From the 2nd semester on
elective
Course type/weekly
hours:
Tutorial: 2 h (weekly)
Tutoring groups of up to 20 students
Total workload:
A tutor assists a course (usually basic or core lectures) for one
semester. This includes the following tasks:
•
•
•
•
•
•
•
•
•
Learning the specific didactic aspects of the course matter
(4h).
Moderating the weekly meetings (90 min each) of a tutorial
group
Correction of weekly tests, taken in the group
Weekly office hours (90 min) for students attending the
course.
Attending weekly team-meetings with all tutors and
lecturers of the course (45 min)
Participation in developing sample exercise solutions of the
weekly assignments (90 min weekly)
Answering incoming questions on the mailing list regarding
topics of the course and the weekly assignments (60 min
weekly)
Getting to grips with the contents of the current lecture (2h
weekly)
Creating new exercises (1h weekly)
Supervising and correcting exams
Credits:
4
Entrance requirements:
Each lecturer selects the tutors for his courses. A prerequisite
for becoming a tutor is a very good grade in the relevant
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course, interest in didactics and an observable talent for
didactical work.
Aims/Competences to be
developed:
Tutors learn how courses are being organized and which
methodical aims are being followed. They learn how to
communicate complex scientific subject matters to larger
groups and in individual meetings.
Before starting their work the students attend one or more
colloquia in which they are introduced to the specific didactic
aspects of the course matter.
In assisting the course, they learn how to adapt to the different
background knowledge and intellectual capicities of the
attending students. They get encouraged to communicate
complex contexts in a concise and effective way. In addition
they get used to communicating subject matters in English.
Content:
See above
Assessment/Exams:
The lecturer supervises tutors and gives them feedback
regarding their contributions to weekly assignments (creating,
finding sample solutions for exisiting eercises), answers to
questions on the mailing list as well as correcting the exams.
The assistant of the course visits each tutorial once a semester
and gives feedback to the tutor as well as to the lecturer. At the
end of the semester each students evaluates the work of
his/her tutor as a part of the course evaluation.
Used media:
Paper and blackboard
Literature:
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Module: Seminar
Program of Studies:
Master Program Bioinformatics
Name of the module:
Seminar about bioinformatical topics
Abbreviation:
S-M-1
Subtitle:
Changing Topics
Modules:
2 h weekly
Semester:
offered each semester
Responsible lecturer:
relevant Professor
Lecturer:
Lecturers of Computational Chemistry
Language:
German / English
Level of the unit/
Mandatory or not :
Graduate course/ Mandatory Elective
Course type/weekly
hours:
Total workload:
Seminar 2 SWS (bis zu 25 Studierende)
Credits:
7
Entrance requirements:
Basic knowledge in the field of computer science under focus in
the respective seminar.
Aims/Competences to
be developed:
At the end of the course students have gained a thorough
knowledge of current or foundational aspects of a specific area in
computer science.
210 h = 32 h classes and 178 h private study
They attained competences in independently investigating,
classifiying, summarizing, discussing, criticizing scientifc issues
and presenting scientific findings.
Content:
Practical exercising of
•
Reflecting on scientific work,
•
Analyzing and assessing scientific papers
•
Composing scientific abstracts
•
Discussing scientific work in a peer group
•
Developing common standars for scientific work
•
Presentation techniques
Specific focus according to the individual topic of the seminar
Typical course progression:
• Preparatory meetings to guide selection of individual
topics
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•
Repetitive meetings with discussions of selected
contributions
• Talk and elaboration on one of the contributions
Oral exam on entire scientific area spanned by the seminar
Assessment/Exams:
•
•
•
•
Contributions to discussions
Thematic talk
Written elaboration
Final oral examination on the entire scientific area
spanned by the seminar
Used media:
•
Discussions during class
Talks based on slides
Literature:
According to the topic
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Module: Master Seminar
Program of Studies:
Master Program Bioinformatics
Name of the module:
Master Seminar
Abbreviation:
MS-M-1
Modules:
Every time possible
Responsible lecturer:
Relevant lecturer
Lecturer:
Lecturers who are allowed to supervise a master thesis
Language:
English
Level of the unit/
Mandatory or not :
3rd Semester MSc
Compulsory
Course type/weekly
hours:
Seminar 1 h (weekly)
Practical: 3 h (weekly)
Total workload:
360 h private study
Credits:
12
Entrance requirements:
All mandatory modules except Master seminar and Master thesis
Aims/Competences to
be developed:
The Master seminar sets the ground for carrying out independent
research within the context of an appropriately demanding
research area. This area provides sufficient room for developing
own scientific ideas.
At the end of the Master seminar, the basics ingredients needed
to embark on a succesful Master thesis project have been
explored and discussed with peers, and the main scientific
solution techniques are established.
The Master seminar thus prepares the topic of the Master thesis.
It does so while deepening the students’ capabilities to perform a
scientific discourse. These capabilities are practiced by active
participation in a reading group. This reading group explores and
discusses scientifically demanding topics of a coherent subject
area.
Content:
The methods of computational biology are systematically
applied, on the basis of the "state-of-the-art".
Assessment/Exams:
Written description of the topic of the Master thesis.
Presentation of the planned thesis topic followed by a plenary
discussion .
Depending on the topic
Depending on the topic
Used media:
Literature:
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Module: Master Thesis
Program of Studies:
Master Program Bioinformatics
Name of the module:
Master Thesis
Abbreviation:
Subtitle:
topics are offered each semester
Modules:
The relevant Professor
Dozent(in):
Lecturers who are allowed to supervise a master thesis
Sprache:
English
Level of the unit/
Mandatory or not :
4th Semester MSc
Compulsory
Course type/weekly
hours:
Total workload:
900 h private study
Credits:
30
Entrance requirements:
Master Seminars
Aims/Competences to
be developed:
In the master thesis the student demonstrates his ability to perform
independent scientific work focusing on an adequately challenging
topic prepared in the master seminar.
On the basis of the "state-of-the-art", bioinformatic methods are
applied to strive for novel bioinformatic findings, and this application
is documented systematically.
Content:
Assessment/Exams:
Written elaboration in form of a scientific paper. It describes the
scientific findings as well as the way leading to these findings.
It contains justifications for decisions regarding chosen methods for
the thesis and discarded alternatives. The student’s own substantial
contribution to the achieved results has to be evident. In addition,
the student presents his work in a colloquium, in which the scientific
quality and the scientific independence of his achievements are
evaluated.
Literature:
According to the topic
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