| Area of Mathematics: | Computational and Applied Mathematics (ECAM) | ||
| Semester: | 5ο | ||
| Course ID: | 52402 | ||
| Course Type: | Elective | ||
| Teaching hours per week: | Theory: 3 | Practice: 0 | Laboratory: 1 |
| ECTS : | 5 | ||
| Eclass: | |||
| Instructors: | Bagos Pantelis | ||
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.
- Neil C. Jones, Pavel A. Pevzner, An Introduction to Bioinformatics Algorithms (Computational Molecular Biology), 1st edition, MIT Press, 2004.
- Richard Durbin, Sean R. Eddy, Anders Krogh and Graeme Mitchison, Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids, Cambridge University Press, 1998.
