Bioinformatics II (6ΕΒ05)
Instructor : Pantelis Bagos
Assistant : Kontou Panagiota
Course typeElective
Semester6
TermSpring Semester
ECTS5
Teaching hours3
Laboratory hours1
Description
Algorithms in Bioinformatics: Dynamic Programming in Bioinformatics, Algorithms for Local and Global Alignment, The Algorithms of Needleman-Wunch, Smith-Waterman, Gotoh and variants. Other Applications of Dynamic Progrmming, Hidden Markov Models in Bioinformatics, Forward and Backward Algorithms, Decoding Algorithms (Viterbi, NBest, Posterior, Posterior-Viterbi, OAPD), Parameter Estimation using Baum-Welch and Gradient Descent Algorithms, Class HMMs, Algorithms for Labeled Sequences, Algorithms for Incorporation of Experimental Information in HMMs, profile HMMs. Heuristic Methods in Bioinformatics, The Gumbel’s Extreme Value Distribution and its Application in Bioinformatics, Clustering Methods in Bioinformatics, Genetic Algorithms in Bioinformatics, Neural Networks in Bioinformatics. The PERL Programming Language (Scalar Variables, Operators, Lists, Arrays, Hashes, Control Structures, I/O, Pattern Matching and Regular Expressions), Applications in Bioinformatics. Special Topics in Bioinformatics (Comparative Genomics, Functional Genomics, Structural Genomics)
Course objectives

After completing the course, students are expected to:

  • Be able to solve more complex problems related to genomics, biological networks and gene expression
  • Be able to program in Perl and create simple programs for sequence analysis, pattern matching and prediction.
Textbooks/Bibliography
  • Εισαγωγή στους Αλγόριθμους Βιοπληροφορικής, NEIL C. JONES, PAVEL A. PEVZNER, ΕΚΔΟΣΕΙΣ ΚΛΕΙΔΑΡΙΘΜΟΣ ΕΠΕ, 1η/2010, ΑΘΗΝΑ
  • Οδηγός της Perl, Pierce Clinton, Χ. ΓΚΙΟΥΡΔΑ & ΣΙΑ ΕΕ, 1η έκδ./2005, ΑΘΗΝΑ
Assessment method
Written examinations
Course material
http://eclass.uth.gr/eclass/courses/DIB131/