Computational Biochemistry course in Zurich

Gaston Gonnet gonnet at inf.ethz.ch
Wed Aug 5 05:05:54 EST 1992


                                Compact course:
                                ===============

                          COMPUTATIONAL BIOCHEMISTRY: 
              PROTEIN SEQUENCE ANALYSIS AND STRUCTURE PREDICTION

                      ETH Zurich, IFW A 32, 17./18.9.92


Goals:
======

The explosion in the size of protein sequence databases presents new 
opportunities for understanding the structure, function, and evolution
of proteins. This course will provide the mathematical and algorithmic
principles for organizing and analyzing homologous protein sequences.
This will involve hands-on experience with the computer system DARWIN,
which facilitates computational biochemistry. The course concludes by
describing the application of sequence analysis to the de novo
prediction of the folded structure of proteins.

Contents:
=========

1.  Introduction
1.1 Terminology
1.2 Background: Computer science, statistics, biochemistry, 
    and computational biochemistry
1.3 Potential application of results from computational biochemistry

2.  Protein Sequence Alignment
2.1 Natural organization of protein sequences: 
    Evolutionary relationships
2.2 Models of mutation: Mutation matrices and PAM distances
2.3 Dynamic programming algorithms and simplified variations
2.4 Estimating PAM distances
2.5 Modelling insertions and deletions
2.6 Aligning DNA sequences against both DNA and protein sequences
2.7 All-against-all matching

3.  Pattern Recognition in Sequences
3.1 Maximum repetitions
3.2 K-gram repetition
3.3 Prosite-style patterns and pattern searching
3.4 One-against-all matching

4.  Phylogenetic trees
4.1 Reconstruction of the topology of phylogenetic trees
4.2 Evolutionary phylogenetic trees
4.3 Probabilistic ancestral sequences
4.4 Multiple alignments

5.  Predicting de novo the Folded Structure of proteins
5.1 Surface, interior, and parsing algorithms
5.2 Active site algorithms
5.3 Predicting secondary structure
5.4 Assembling the secondary structural units to give
    a tertiary structure
5.5 Protein kinase: a success story

6.  Databases and tools
6.1 Available databases
6.2 Introduction to the DARWIN system

Programme:
==========

Thursday September 17:

08.30 Introduction
09.00 Theory of sequence alignment
10.00 Coffee break
10.30 Methods of sequence alignment
11.45 Lunch
13.15 Results of exhaustive matching
      Pattern matching and new insights into protein structure
15.00 Coffee break
15.30 Overview of the DARWIN system
16.00 Hands-on Database searching

Friday September 18:

08.30 Phylogeny
09.00 Multiple sequence alignments
10.00 Coffee break
10.30 Protein Structure Prediction I: Surface, inside, parse
11.45 Lunch
13.15 Protein Structure Prediction II:
      Secondary and tertiary structure
15.00 Coffee break
15.30 Advanced computational techniques
16.15 Hands-on use of DARWIN
17.30 End of course

Language:
=========

The course as well as the materials, will be in English.


Lecturers:
==========

Prof. Dr. Gaston H. Gonnet, Scientific Computation
Prof. Dr. Steven A. Benner, Bio-organic Chemistry



ETH has a tradition of offering compact courses in Computer Science
and applications.  These courses are 2/3-day intensive courses,
typically with hands-on experience and are geared towards the
professionals who work in the field and want to be updated with
state of the art practices.


For information and registration write, fax or e-mail:

Departement Informatik, ETH Zurich, Fortbildungskurse
Frau M. Bernard,
ETH Zentrum, 8092 Zurich.
Tel: (41) 1 254 7206,  Fax: (41) 1 262 3973
E-mail: bernard at inf.ethz.ch or oetting at inf.ethz.ch




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