An introduction to
Bioinformatics Algorithms
Qi Liu
email: qi.liu@vanderbilt.edu
Presented by Liu Qi
Description of the Course

introduce the basic computational issues and
methods used in molecular biology
 Topics will include basic algorithms for
alignment of biological sequences and
structures. These include, for example,
dynamic programming algorithms for
alignment, motif definition and computation,
Hidden Markov Models, neural networks etc.
Presented By Liu Qi
Related Courses

University of Washington （Computational Biology)


Tel Aviv University School of Computer Science
(Algorithms in Molecular Biology )


http://www-helix.stanford.edu/courses/bmi214/
MIT(Foundations of Computational and Systems Biology)


http://www.cs.tau.ac.il/~rshamir/algmb/algmb-archive.htm
Stanford(Representations and Algorithms for
Computational Molecular Biology )


http://www.cs.washington.edu/education/courses/527/09au/
http://ocw.mit.edu/courses/biology/7-91j-foundations-ofcomputational-and-systems-biology-spring-2004/
Imperial College (Introduction to Bioinformatics)

http://www.doc.ic.ac.uk/~sgc/teaching/341/
Presented By Liu Qi
Reference Books




An Introduction to Bioinformatics Algorithms
Neil C. Jones and Pavel A. Pevzner
Bioinformatics: The Machine Learning Approach
by Baldi, Pierre. Brunak, Søren.
Bioinformatics: Sequence and genome analysis
(cold spring harbor laboratory press) Mount,
David W.
Biological sequence analysis: Probabilistic
models of proteins and nucleic acids
(Cambridge university press) R. Durbin et al.
Presented By Liu Qi
Content
Pairwise Sequence Alignment
 Multiple sequence alignment
 Motif discovery
 Protein secondary structure prediction
 Microarrays, Clustering and Classification
 Topics for Discussion

Presented By Liu Qi
Pairwise Sequence alignment
Dot matrix (intuitive)
 Dynamic programming (exact)

Global Needleman-Wunsch
 Local Smith-Waterman


Word or k-tuple (heuristic)
FASTA
 BLAST

Presented By Liu Qi
Multiple sequence alignment
Dynamic Programming
 Heuristic Alignment Methods


Progressive alignment
 clustalw


Iterative refinement
Hidden Markov Model
Presented By Liu Qi
Motif discovery
Greedy Search
 Expectation Maximization
 Gibbs sampler
…

Presented By Liu Qi
Protein secondary structure
prediction
Chou-Fasman predictions
 Garnier, Osguthorpe and Robson
 Neural networks
 Nearest neighbor methods
 Consensus prediction approaches

Presented By Liu Qi
Microarrays, Clustering and
Classification
Normalization
 Differential Expression Genes Detection
 Clustering

– Hierarchical
 – K-means
 – SOM

Class Prediction
 Integrating other Biological Knowledge

Presented By Liu Qi
Topics for Discussion
Proteomics data analysis
 NGS Data Analysis
 Integrative analysis of various omics data
 …..

Presented By Liu Qi