Bioinformatics I (5KB04)
Instructor : Pantelis Bagos
Assistant : Kontou Panagiota
Course typeCompulsory
Semester5
TermFall Semester
ECTS5
Teaching hours3
Laboratory hours1
Description
Definition of Bioinformatics, Data types in Bioinformatics, Databases: Scientific Literature Databases, Sequence Databases, Structure Databases, Fold databases. Information retrieval systems and Database Management systems (SRS, Entrez). Sequence Alignment: Sequence Homology and Sequence Similarity, Dynamic Programming, Global Alignment and the Needleman-Wunch algorithm, Local Alignment and the Smith-Waterman algorithm, The Statistical Significance of Local Alignments, Substitution Matrices, Gap Penalties, Heuristic Alignment Methods (FASTA, BLAST). Multiple Sequence Alignment, Multidimensional Dynamic Programming Algorithms, Heuristic Methods (CLUSTAL, DIALIGN, MULTALIN etc), Phylogenetic Inference and Multiple Alignments, Prediction Algorithms Using Protein and DNA Sequences: Prediction of Protein and RNA Secondary Structure, Prediction of Transmembrane Segments of Proteins, Gene Finding, Multiple Alignments Using Hidden Markov Models, Protein Classification. Structural Bioinformatics: Representation of Protein Structures, Protein Fold Recognition, Structure Superposition, Homology Modelling, Threading.
Course objectives

After completing the course, students are expected to:

  • Be able to recognize and understand more complex biological phenomena, in which bioinformatics is implicated
  • Be able to solve problems related to database searches
  • Be able to use basic tools for sequence alignment, multiple alignment and protein structure prediction
Textbooks/Bibliography
  • Βιοπληροφορική, OVELLETE F. - BAXEVANIS A., ΠΑΡΙΣΙΑΝΟΥ ΑΝΩΝΥΜΗ ΕΚΔΟΤΙΚΗ ΕΙΣΑΓΩΓΙΚΗ ΕΜΠΟΡΙΚΗ ΕΤΑΙΡΙΑ ΕΠΙΣΤΗΜΟΝΙΚΩΝ ΒΙΒΛΙΩΝ, 2η Έκδ./2012, ΑΘΗΝΑ
Assessment method
Written examinations
Course material
http://eclass.uth.gr/eclass/courses/DIB160/