Computational approaches to functional genomics
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The lecture discusses computational approaches for dealing with sequence data and state of the art methods to understand functional roles of biomolecules.
The slides discusses mechanisms like multiple sequence alignment, motifs, profiles and moves on to classifying sequences into super-families, families and sub-families. The presentation dwells further for predicting and quantifying key fingerprints and residues having important repercussions on function of the gene product.
The lecture is supported by solved case-studies which participants can work through for getting hands-on experience in solving interesting biological problems. |
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| Improving multiple alignments using family data; introducing Clustal and Jalview; measuring alignment quality, improving the alignment, features to look for, key residue conservation and functional motifs |
 Lecture (2.98 MB)
 Exercises, Answers |
| Sequence-based protein classification databases: ADDA, Pfam, Prosite, InterPro, E-Motif/3D-Motif. |
Lecture (1.30 MB)
Exercises, Answers |
| Introduction to phylogenomics: functional and evolutionary analysis using eukaryotic linear motifs, PipeAlign, and Mega. |
Lecture (786 KB)
Exercises, Answers |
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