Algorithmic Bioinformatics

1
Algorithmic Bioinformatics
2
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

3
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.
• 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

4
Book

• Protein Bioinformatics by Eidhammer et al.
• Chapters on
• sequence alignment,
• multiple sequence alignment, and
• structure alignment

5
Structure of module

• Algorithms for Sequences
• Sequence comparison
• Multiple sequence alignment
• Algorithms for Structures
• Intro to structures
• Superposition
• Geometric techniques
• Clustering
• Advanced topics
• Scoppi and Interaction interfaces
• HMM and prediction of interactions
• Structure prediction
• Docking
• Atomic force microscopy and bioinformatics
• Textmining
• Revision

Good news Conceptually You know most of the
topics We will cover
Bad news Its a long way to understand all the
details
6
Labs

• Annalisa and Frank will run the labs.
• If you have any questions then contact him on
• Frank.dressel_at_biotec.tu-dresden.de
• 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)

8
Assessment

• Lecture Exam, which counts 80
• Lab
• Programming task in pairs 20
• Will be handed out during term

9
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

10
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