EE550

Computational Biology

 

Meeting times             : Thursday 13:30, 14:30, 15:30

Instructor                   : Bilge Karaçalı, PhD

Office                          : EEE Building Room 219

E-mail                         : bilge@iyte.edu.tr

 

Summary

This course will begin with a broad description of cellular organization in a molecular biology perspective including nucleic acid and protein structure. Computational methods for pattern detection and clustering will be introduced in the analysis of amino acid sequences of proteins. Probabilistic models of genetic evolution will be developed along with sequence alignment and motif detection algorithms. RNA and DNA analysis with microarrays will be discussed. Dynamic modelling of gene transcription networks will be introduced.

 

Grading

Midterm           20%

Final                 30%

Homework       20%

Project             30%

 

Term Project

 

Homeworks

Homework 1 – due 15.03.2018

Homework 2 – due 29.03.2018

Homework 3 – due 26.04.2018

 

Tests

Midterm

Final

 

Material

 

Syllabus

 

Week 1: Introduction to computational biology

 

Week 2: Nucleic acid and protein structure

 

Week 3: Evolution mechanism through mutations

 

Week 4: Probabilistic amino acid sequence evolution models

 

Week 5: Gene and protein databases

 

Week 6: Sequence alignment

 

Week 7: Searching sequence databases

 

Week 8: Inter-species evolutionary relationships via phylogenetic trees

 

Week 9: Optimality criteria in phylogenetic tree construction

 

Week 10: Pattern searching in functional protein groups: Sequence motifs

 

Week 11: Bioinformatics

 

Week 12: Microarray data analysis

 

Week 13: Systems biology – Gene transcription networks

 

Week 14: Regulation of gene transcription

 

Data files