Transcript Algorithmic Bioinformatics

Algorithmic Bioinformatics
Michael Schroeder
BioTechnological Center
TU Dresden
Biotec
Bioinformatics cycle
 Applied bioinformatics
 Use bioinformatics tools
 Access databases and tools over the web
 Programming for bioinformatics
 Learn programming skills relevant to bioinformatics
 Algorithmic bioinformatics
 Develop bioinformatics tools
By Michael Schroeder, Biotec
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Syllabus
 The module covers algorithms and data structures for
bioinformatics. It will cover:
 sequences (DNA and amino acid sequences).
 structure (structure comparison and alignment)
 For each of these data types the module will cover important
algorithms to manipulate and analyse the data.
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 Students will appreciate the different types of data mostly generated
in bioinformatics
 Students will understand how to analyse the different types of data
 Students will be able to design data structures and algorithms to
analysis bioinformatics data
 Students will be able to critically assess quality of algorithms
 Students will be able to write basic programmes
By Michael Schroeder, Biotec
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Book
 Protein Bioinformatics by
Eidhammer et al.
 Chapters on
 sequence alignment,
 multiple sequence
alignment, and
 structure alignment
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Structure of module
 Algorithms for Sequences
 Sequence comparison
 Multiple sequence alignment
 Algorithms for Structures
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Intro to structures
Superposition
Geometric techniques
Clustering
 Advanced topics
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Good news: Conceptually
You know most of the topics
We will cover
Bad news: It’s a long way
to understand all the details
Scoppi and Interaction interfaces
HMM and prediction of interactions
Structure prediction
Docking
Atomic force microscopy and bioinformatics
Textmining
Revision
By Michael Schroeder, Biotec
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Labs
 Annalisa and Frank will run the labs.
 If you have any questions then contact him on:
 [email protected]
 Style
 Programming,
 paper and pencil,
 use programmes
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Lab Contents
 Local and global sequence alignments
 Phylogeny and clustering
 Finding and highlighting sequence motifs in PDB
structures
 Distance plots for inter-atomic distances
 (Using programmes for docking, molecular modelling,
gene expression data analysis, textmining)
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Assessment
 Lecture: Exam, which counts 80%
 Lab:
 Programming task in pairs 20%
 Will be handed out during term
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Assessment
 Homework is mandatory!
 Each week you will be given tasks to complete for the
following week. You will not be marked on the
homework, but you must hand it in
 Handing in of homework is pre-requisite for the
programming task
 no homework = no marks
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Preparation for labs and lectures
 Get Book
 Read Book
 Read all slides from term 1 again
 Read all slides from term 2 again
 Do all programming labs of term 2 again, especially
 Dot plots
 Sequence alignments
 Residue counts
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