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Michael Schroeder BioTechnological Center TU Dresden Biotec Discrete Algorithms for Computational Biology Gene Myers, MPI-CBG Michael Schroeder, Biotec, TUD Dresden Michael Hiller, MPI-CBG

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Page 1: Michael Schroeder BioTechnological Center TU Dresden Biotec Discrete Algorithms for Computational Biology Gene Myers, MPI-CBG Michael Schroeder, Biotec,

Michael Schroeder BioTechnological CenterTU Dresden Biotec

Discrete Algorithms for Computational Biology

Gene Myers, MPI-CBGMichael Schroeder, Biotec, TUD Dresden

Michael Hiller, MPI-CBG

Page 2: Michael Schroeder BioTechnological Center TU Dresden Biotec Discrete Algorithms for Computational Biology Gene Myers, MPI-CBG Michael Schroeder, Biotec,

By Michael Schroeder, Biotec 2

Bioinformatics

BIOlogy

matheMATICS

INFORmatics

Page 3: Michael Schroeder BioTechnological Center TU Dresden Biotec Discrete Algorithms for Computational Biology Gene Myers, MPI-CBG Michael Schroeder, Biotec,

By Michael Schroeder, Biotec 3

Bioinformatics

Bioinformatics = Biological + Informatics

Page 4: Michael Schroeder BioTechnological Center TU Dresden Biotec Discrete Algorithms for Computational Biology Gene Myers, MPI-CBG Michael Schroeder, Biotec,

By Michael Schroeder, Biotec 4

Bioinformatics

Bioinformatics = Biological + Informatics - Logical

Page 5: Michael Schroeder BioTechnological Center TU Dresden Biotec Discrete Algorithms for Computational Biology Gene Myers, MPI-CBG Michael Schroeder, Biotec,

Synopsis

Computational problems and algorithmic solutions for genomic data Pre-requesite: Data structure and basic algorithms

Goal: (a) able to design a dynamic programming (b) understand sequence comparison and Hidden

Markov Model methods (c) understand, use, and programme sequence-based

bioinformatics

By Michael Schroeder, Biotec 5

Page 6: Michael Schroeder BioTechnological Center TU Dresden Biotec Discrete Algorithms for Computational Biology Gene Myers, MPI-CBG Michael Schroeder, Biotec,

Part 1: Sequence comparison

Week 1: Primer on Molecular Biology Week 2-5: Sequence Comparison, theory and

practice The basic dynamic programming algorithm, gap cost

variations, extension to patterns. Acceleration: indexing, filtration methods, FASTA and

BLAST as examples. Multi-sequence alignment: scoring schemes,

greedy/DCA/MSA/round-robin heuristics.

By Michael Schroeder, Biotec 6

Page 7: Michael Schroeder BioTechnological Center TU Dresden Biotec Discrete Algorithms for Computational Biology Gene Myers, MPI-CBG Michael Schroeder, Biotec,

Part 2: Gene Finding

Week 6-9: Gene Finding Approaches: statistical, homology-based, Bayesian via

Hidden Markov Models. Hidden Markov Models (HMMs): Viterbi and

forward/backward algorithms

By Michael Schroeder, Biotec 7

Page 8: Michael Schroeder BioTechnological Center TU Dresden Biotec Discrete Algorithms for Computational Biology Gene Myers, MPI-CBG Michael Schroeder, Biotec,

Part 3: Phylogeny

Week 10-13: Phylogeny Jukes-Cantor model, maximum-likelihood method,

distance-based methods, neighbor-joining, HMMs. Genome rearrangements

By Michael Schroeder, Biotec 8

Page 9: Michael Schroeder BioTechnological Center TU Dresden Biotec Discrete Algorithms for Computational Biology Gene Myers, MPI-CBG Michael Schroeder, Biotec,

Part 4: Optional topics

Week 14: Optional Topics (per instructor and time permitting) RNA Secondary Structure: Definitions, Scoring

schemes, dynamic programming approaches. Motif Finding: Repeat finding. Promoter and enhancer

recognition. Signal peptide recognition. Genotyping: Basic genetics, haplotype determination,

haplotype blocks, forensic identification. Genome Sequence Assembly: Technology overview.

Overlap-layout-consensus paradigm. Approaches.

By Michael Schroeder, Biotec 9

Page 10: Michael Schroeder BioTechnological Center TU Dresden Biotec Discrete Algorithms for Computational Biology Gene Myers, MPI-CBG Michael Schroeder, Biotec,

By Michael Schroeder, Biotec 10

Getting in touch

Email: [email protected]

Web site: http://www.biotec.tu-dresden.de/schroeder

Page 11: Michael Schroeder BioTechnological Center TU Dresden Biotec Discrete Algorithms for Computational Biology Gene Myers, MPI-CBG Michael Schroeder, Biotec,

By Michael Schroeder, Biotec 11

Useful books