Bioinformatics I

 Definition and History 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, Hidden Markov Models and Neural Networks 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.

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

• ΒΙΟΠΛΗΡΟΦΟΡΙΚΗ, ΜΠΑΓΚΟΣ ΠΑΝΤΕΛΕΗΜΩΝ, “Ελληνικά Ακαδημαϊκά Ηλεκτρονικά Συγγράμματα και Βοηθήματα – Αποθετήριο “”Κάλλιπος”””, 1η/2016, ΑΘΗΝΑ, 59303485
• Βιοπληροφορική, OVELLETE F. – BAXEVANIS A., “ΠΑΡΙΣΙΑΝΟΥ ΑΝΩΝΥΜΗ ΕΚΔΟΤΙΚΗ ΕΙΣΑΓΩΓΙΚΗ ΕΜΠΟΡΙΚΗ ΕΤΑΙΡΙΑ ΕΠΙΣΤΗΜΟΝΙΚΩΝ ΒΙΒΛΙΩΝ”,      2η Έκδ./2012, ΑΘΗΝΑ, 22771922

 Written examinations

http://eclass.uth.gr/eclass/courses/DIB160/