Computational Biology


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

Instructor                   : Bilge Karaçalı, PhD

Office                          : EEE Building Room 219

E-mail                         :



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.



Midterm           20%

Final                 30%

Homework       20%

Project             30%


Term Project



Homework 1 – due 15.03.2018

Homework 2 – due 29.03.2018

Homework 3 – due 26.04.2018










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