Center for Bioinformatics Saarland University Module Descriptions

Module Descriptions of the Master Program Bioinformatics, Saarland University 1

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


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: Core Lectures Computer Science

Program of Studies:


Name of the module:

Data Structures and Algorithms

Abbreviation:

I-M-1

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. Kurt Mehlhorn

Lecturer:

Prof. Dr. Kurt Mehlhorn, Prof. Dr. R. Seidel, Dr. Ernst Althaus, Dr. Ulrich Meyer

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: 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.


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, branch-and-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:

Slides, beamer

Literature:

- 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.


Program of Studies:


Name of the module:

Computer Graphics

Abbreviation:

I-M-2

Subtitle:

Core lecture


Semester:



Prof. Dr. Philipp Slusallek

Lecturer:

Prof. Dr. Philipp Slusallek, Prof. Dr. Hans-Peter Seidel, Dr. Marcus Magnor

Language:

English





Total workload:


Credits:

9


For graduate students: none .


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 hardware-based visualization application. A final rendering competition allows students to implement their favorite advanced algorithm and use it in a high-quality rendering.


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 - Homogeneous coordinates - Hardware architectures - Rendering pipeline - Shader programming and languages - OpenGL

Assessment/exams: - 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


Program of Studies:


Name of the module:

Database Systems

Abbreviation:

I-M-3

Subtitle:

Core lecture


Semester:



Prof. Dr. Jens Dittrich

Lecturer:

Prof. Dr. Jens Dittrich, Prof. Dr. Gerhard Weikum

Language:

English





Total workload:


Credits:

9


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").



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 time-tested 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, nested-

loop-, - 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


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


Program of Studies:


Name of the module:

Information Retrival and Data Mining

Abbreviation:

I-M-4

Subtitle:

Core lecture


Semester:



Prof. Dr. Gerhard Weikum

Lecturer:

Prof. Dr. Gerhard Weikum

Language:

English





Total workload:


Credits:

9


For graduate students: none


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.


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


Program of Studies:


Name of the module:

Artificial Intelligence

Abbreviation:

I-M-5

Subtitle:

Core lecture


Semester:

1st -3rd Semester / At least once every two years


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 :




Total workload:


Credits:

9




Knowledge about the fundamentals of artificial intelligence


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


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


Program of Studies:


Name of the module:

Optimization

Abbreviation:

I-M-6

Subtitle:

Core lecture


Semester:



Dean Computer Science

Lecturer:

Dr. Fritz Eisenbrand

Language:

English





Total workload:


Credits:

9




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


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


Program of Studies:


Name of the module:

Geometric Modelling

Abbreviation:

I-M-7

Subtitle:

Core lecture


Semester:



Prof. Dr. Hans-Peter Seidel

Lecturer:

Prof. Dr. Hans-Peter Seidel, Prof. Dr. Philipp Slusallek

Language:

English





Total worload:


Credits:

9




Learning working knowledge of theoretical and practical methods for solving geometric modeling problems on a computer.


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%)


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


Program of Studies:


Name of the module:

Introduction to Computational Logic

Abbreviation:

I-M-8

Subtitle:

Core lecture


Semester:



Prof. Dr. Gert Smolka

Lecturer:

Prof. Dr. Gert Smolka

Language:

English





Total worload:


Credits:

9




- 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


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


Program of Studies:


Name of the module:

Image Processing and Computer Vision

Abbreviation:

I-M-9

Subtitle:

Core lecture




Lecturer:

Prof. Dr. Joachim Weickert

Language:

Prof. Dr. Joachim Weickert

Sprache:

English





Total workload:


Credits:

9




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.


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


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.


Program of Studies:


Name of the module:

Software Engineering

Abbreviation:

I-M-10

Subtitle:

Core lecture


Semester:



Prof. Dr. Andreas Zeller

Lecturer:

Prof. Dr. Andreas Zeller

Language:

English





Total workload:


Credits:

9




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.


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


Used Media: Slides, beamer, presentations with laptop, labs using computer

Literature: - Balzert, Softwaretechnik I and II - Own lecture notes


Module: Advanced Lectures of Life Sciences Program of Studies:


Name of the module:

Molecular Biotechnology 2

Abbreviation:

B-M-1

Subtitle:

Modules:

Lecture: Molecular Biotechnology 2

Semester:

2nd Semester, Summer Semester


Prof. Dr. Rita Bernhardt

Lecturer:

Prof. Dr. Rita Bernhardt

Language:

German




Lecture: 2 h

Total workload:


Credits:

3


Biochemistry 1 and 2, Molekular Biotechnology 1


Knowledge of the methods of the genetic mutation of productive organisms

Content: - 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

Assessment/Exams: Written exam, protocols


Program of Studies:


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


Prof. Dr. Eckart Meese

Lecturer:

Prof. Dr. Eckart Meese, Prof. Dr. Cornelius Welter

Language:

German




Lecture: 2 h (weekly)

Total workload:


Credits:

3


Familiarity with the basics of genetics


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.


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, re-exam 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


Program of Studies:


Name of the module:

Systems and Synthetic Biology (former: Functional Genomics and Metabolic Engineering)

Abbreviation:

B-M-4

Subtitle:

-

Modules:

Lecture, tutorial, and seminar

Semester:

Once every two years


Prof. Dr. Elmar Heinzle

Lecturer:

Prof. Dr. Elmar Heinzle, Dr. Fozia Noor

Language:

English




Lecture: 2 h (weekly) Tutorial: 1 h (weekly) Seminar: 1 h (weekly)

Total workload:

180 h = 60 h of classes and 120 h private study and assignments

Credits:

6


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


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. Introduction to Systems and Synthetic Biology 2. Metabolic networks 3. Regulatory networks 4. Reaction networks – network models and -design 5. Analysis – genome, transcriptome, proteome,

metabolome 6. Quantitative proteome analysis 7. Metabolome analysis 8. Metabolic flux analysis (fluxome) 9. Genetic engineering 10. Modeling of metabolic networks / Metabolic control

analysis 11. Production of primary metabolites 12. Production of secondary metabolites 13. Protein production 14. 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


Program of Studies:


Name of the module:

Bio-Reaction Engineering

Abbreviation:

B-M-5

Subtitle:

-

Modules: Lecture, tutorial, and seminar

Semester:

1st – 3rd semester / every winter semester



Lecturer:


Language:

English




Lecture: 2 h (weekly) Tutorial: 1 h (weekly) Seminar: 1 h (weekly)

Total workload:


Credits:

6


Basic knowledge mathematics, biochemistry


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.


Content:

1. Thermodynamics of biological processes 2. Mass and energy balances 3. Enzyme kinetics 4. Growth kinetics 5. Kinetics of cellular processes 6. Metabolic balances 7. Material transport 8. Bioreactors GL 9. 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


Program of Studies:


Name of the module:

Special-topic Lecture Biosciences: Virology and Immunology

Abbreviation:

B-M-6

Modules: Lecture

Semester:

1st – 3rd semester / every winter semester


Prof. Dr. Hagen von Briesen

Lecturer:

Prof. Dr. Hagen von Briesen

Language:

English




Lecture: 2 h (weekly)

Total workload:


Credits:

3


Basic knowledge in molecular biology


Advanced knowledge in Virology and Viral Immunology

Content:

- 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

Assessment/Exams: Written exam

Methods:

Lecture, film presentations, written tests, excursion to the “HIV Specimen Cryorepository”


Program of Studies:


Name of the module:

Special-topic Lecture Biosciences: Advances in Drug Delivery: Vaccination

Abbreviation:

B-M-6

Modules:

Advances in Drug Delivery: Prospects for Vaccination

Semester:

1st-4th semester, every summer term


Dr. Eva Collnot

Lecturer:

Dr. Eva Collnot, Dr. Steffi Hansen, Dr. Nicole Daum, Dr. Brigitta Loretz

Language:

English


Graduate course / mandatory elective - Advanced Lectures of Life Sciences


Lecture and seminar: 2h (weekly)

Total workload:

90 h = 30 h in class and 60 h private study and assignments

Credits:

3


Bachelor degree in science.


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


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


Program of Studies:


Name of the module:

Special-topic Lecture Biosciences: Bioanalytics

Abbreviation:

B-M-6

Subtitle:

-

Modules:

Lecture and tutorial „Bioanalytics“

Semester:

1st – 3rd semester

Angebotsturnus:


Prof. Dr. Dietrich Volmer

Lecturer:

Prof. Dr. Dietrich Volmer, PD Dr. Ralf Kautenburger

Language:

German




Lecture: 2 h (weekly) Tutorial: 1 h (weekly)

Total workload:


Credits:

5


Basics of instrumental analytics Basics of organic chemistry and biochemistry


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.


Content:

- 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-D-structural 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.

Assessment/Exams: Written exam at the end of the semester


Program of Studies:


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


Prof. Dr. Gregor Jung

Lecturer:

Prof. Dr. Gregor Jung

Language:

German




Lecture: 2 h Tutorial: 1 h (compulsory attendance)

Total workload:

150 h = 45 h of classes and105 h private study

Credits:

5


Physics and physical chemistry, basic knowledge of dynamics, kinetics, spectroscopy and optics are strongly recommended


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).


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: dipole-dipole 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


Program of Studies:


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


Prof. Dr. Volkhard Helms

Lecturer:


Language:

English




Lecture: 2 h Tutorial: 1 h

Total workload:

150 h = 45 h of classes and105 h private study

Credits:

5


Basic knoelegde in genetics and molecular biology


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.

Content:

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

Assessment/Exams: 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.

Literature:

Papers to be distributed in the lecture.


Program of Studies:


Name of the module:

Special-topic Lecture Biosciences: Mechanisms of epigenetic gene regulation

Abbreviation:

B-M-6

Modules:

Lecture

Semester:

1st – 3rd, each summer semester


Prof. Dr. Jörn Walter

Lecturer:

Prof. Dr. Jörn Walter, PD Dr. Martina Paulsen

Language:

English




Block lecture, 3 weeks (2 SWS)

Total workload:


Credits:

3


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.

Content:

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


Literature: C. David Allis, Thomas Jenuwein, Danny Reinberg, Marie-Laure Caparros: Epigenetics, CSHL Press 2007


Program of Studies:


Name of the module:

Special-topic Lecture Biosciences: Medical Biotechnology

Abbreviation:

B-M-6

Modules:

Lecture

Semester:

1st – 3rd, each summer semester


Prof. Dr. Heiko Zimmermann

Lecturer:

Prof. Dr. Heiko Zimmermann, Prof. Dr. Günter Fuhr

Language:

German

Level of the unit/ Mandatory or not:



Lecture: 2 h

Total workload:


Credits:

3


Basic knowledge biochemistry and biology


Advance knowledge biochemistry and biology

Content:

1. Biocompatibility I: Basics 2. Biocompatibility II: Implants 3. Nanobiotechnology I 4. Nanobiotechnology II 5. Electric manipulation of cells 6. Immobilization and encapsulation 7. Cryobiotechnology I: Biophysical and cell biological basics 8. 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

Assessment/exams: Written exam


Program of Studies:


Name of the module:

Special-topic Lecture Biosciences: Systems Toxicology

Abbreviation:

B-M-6

Modules:

Lecture

Semester:

1st – 3rd, winter semester


Dr. Fozia Noor

Lecturer:

Dr. Fozia Noor

Language:

English




Lecture and seminar, 2 SWS

Total workload:


Credits:

3


Basic knowledge in biochemistry, cell biology, systems biology and instrumental analytics


Understanding complex “omics” data and the application of Systems Biology approach to toxicology and human health

Content:

- 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



Module: Advanced Lecture of Bioinformatics Program of Studies:


Name of the module:

Bioinformatics 3

Abbreviation:

BI-M-1

Subtitle:

-

Modules: Lecture and tutorial Bioinformatics 3

Semester:

1st semester / every winter semester



Lecturer:

Prof. Dr. Volkhard Helms, Dr. Tihamér Geyer

Language:

English





Total workload:


Credits:

9


Familiarity with contents of Bioinformatik I and II. The students will have to complete programming assignments with Python.


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"


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)


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


Dr. Oliver Müller

Lecturer:

Dr. Oliver Müller

Language:

English





Total workload:


Credits:

5


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.


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“


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.


Program of Studies:


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


Dr. Marc Hellmuth

Lecturer:

Dr. Marc Hellmuth

Language:

English




Lecture: 2h (weekly) Tutorial: 1h (weekly)

Total workload:


Credits:

5


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.

Content:

- Basics of discrete mathematics - RNA - Reconciliation Trees - Phenotypespaces - Other problems

Assessment/Exams:

About 7 exercises. Participation in the written exam if at least 50 % of all scores of exercises are achieved. Second chance to write exam.

Used Media:

Power point presentation combined with presentations at the blackboard.

Literature:

Special literature that can be downloaded from the webpage of the lecture.


Program of Studies:


Name of the module:

Special Lecture Bioinformatics: Statistical Learning 1

Abbreviation:

BI-BM-1

Subtitle:

-

Modules: Lecture: Statistical Learning 1 Turorial: Statistical Learning 1

Semester:

1st semester master / every summer semester


Prof. Dr. Thomas Lengauer, Ph.D.

Lecturer:

Prof. Dr. Thomas Lengauer, Ph.D.

Language:

English




Lecture: 2 h (weekly) Tutorial: 1 h (two hours every other week)

Total workload:


Credits:

5


Basics of statistics and development of algorithms


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)


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.


Program of Studies:


Name of the module:

Special Lecture Bioinformatics: Statistical Learning 2

Abbreviation:

BI-BM-1

Subtitle:

-

Modules: Lecture: Statistical Learning 2 Turorial: Statistical Learning 2

Semester:

2nd Semester Master/ every summer semester


Dr. Thomas Lengauer, PhD

Lecturer:

Dr. Thomas Lengauer, PhD

Language:

English




Lecture: 2 h (weekly) Tutorial: 1 h (two hours every other week)

Total workload:


Credits:

5


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


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.


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.


Program of Studies:


Name of the module:

Special Lecture Bioinformatics: Next Generation Sequencing

Abbreviation:

BI-BM-1

Subtitle:

Modules: Lecture and Turorial: Next Generation Sequencing

Semester:

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




Lecture: 2 h Tutorial: 1 h

Total workload:


Credits:

5


Recommended are the lectures Bioinformatics 1 and 2, Softwarewerkzeuge der Bioinformatik; basic knowledge of Biology,Genetics, and Biostatistics; proficiency in applying Unix command line


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.


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.

Used media:

The lecture will be presented predominately using electronic slides. Some excercises require access to internet and publically available online databases and software.


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.


Program of Studies:


Name of the module:

Special Lecture Bioinformatics: Modern Methods in Drug Discovery

Abbreviation:

BI-BM-1

Subtitle:

-

Modules: Lecture: 2 h (weekly) Tutorial: 1 h (2 h every second week)

Semester:

1.st semester/ yearly during the winter term


Dr. Michael Hutter

Lecturer:

Dr. Michael Hutter

Language:

English/German




Lecture: 2 h (weekly( Tutorial: 1 h (weekly)

Total workload:


Credits:

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.


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-2011-12/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: Lectures to achieve Key Qualifications Program of Studies:


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


Stiudents dean

Lecturer:


Language:

German


Elective course


Lecture: 1 h, three meetings of 4 h each (afternoon)

Total workload:


Credits:

1


-


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


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"


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


Students´ Dean

Lecturer:

N.N.

Language:

German


Elective course


Lecture/Tutorial: 1 h, three meetings of 4 h each (afternoon)

Total workload:

60 h = 16 h of classes and 44 h of private study

Credits:

1


-


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. - 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


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.


Program of Studies:


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


Students´ Dean

Lecturer:

Axel Koch (Patentverwertungsagentur UdS): Patentrecht; Pia Scherer-Geiß (ZBI): Bioethik

Language:

German


Elective Course


Lecture/Tutorial: 1 h, four or five meetings of 3 h each (afternoon)

Total workload:


Credits:

1


none


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.


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 Online-Patentdatenbanken 5. Praktische Rechercheübung 1. Depatisnet 2. Espacenet

Assessment/Exams:

Attendance to the lecture A short quiz, no grades

Used media:

Powerpoint presentation.

Literature:

-


Module: Advanced Practical Training of Life Sciences Program of Studies:


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


Students´ Dean

Lecturer:

Experimental group leaders of the Center for Bioinformatics or other experimental research groups

Language:

German


Compulsory course


4 weeks full-time

Total workload:

240 h = 160 h of classes and 80 h private study and preparation of the report

Credits:

8


none


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: Tutor Program of Studies:


Name of the module:

Tutor

Abbreviation:

Subtitle:

Modules:

Semester:

Every semester


N.N.

Lecturer:

Qualified students

Language:

German / English

Level of the unit/ Mandatory or not:

From the 2nd semester on elective


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


Each lecturer selects the tutors for his courses. A prerequisite for becoming a tutor is a very good grade in the relevant


course, interest in didactics and an observable talent for didactical work.


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:


Module: Seminar Program of Studies:


Name of the module:

Seminar about bioinformatical topics

Abbreviation:

S-M-1

Subtitle:

Changing Topics

Modules: 2 h weekly

Semester:

offered each semester


relevant Professor

Lecturer:

Lecturers of Computational Chemistry

Language:

German / English


Graduate course/ Mandatory Elective


Seminar 2 SWS (bis zu 25 Studierende)

Total workload:

210 h = 32 h classes and 178 h private study

Credits:

7


Basic knowledge in the field of computer science under focus in the respective seminar.


At the end of the course students have gained a thorough knowledge of current or foundational aspects of a specific area in computer science. 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


• 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


Module: Master Seminar

Program of Studies:


Name of the module: Master Seminar

Abbreviation: MS-M-1

Modules: Every time possible


Relevant lecturer

Lecturer:

Lecturers who are allowed to supervise a master thesis

Language:

English


3rd Semester MSc Compulsory


Seminar 1 h (weekly) Practical: 3 h (weekly)

Total workload:

360 h private study

Credits:

12


All mandatory modules except Master seminar and Master thesis


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 .

Used media: Depending on the topic Literature: Depending on the topic


Module: Master Thesis

Program of Studies:


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


4th Semester MSc Compulsory


Total workload:

900 h private study

Credits:

30


Master Seminars


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.

Content:

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.

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

Documents

Center for Bioinformatics Saarland University Module Descriptions