Introduction to Bioinformatics

One semester, 2 hours lectures 2 hours practicals per week
2 midterm test, Oral or written exam

Lectures

1. Introduction to bioinformatics
   basic concepts, importance, interdisciplinary, core data-types
2. Molecular biology
   primer DNA, gene, replication, transcription, translation, regulation, proteins
3. Algorithms and core operations
   Algorithm analysis, representation, comparison, dot plots
4. Databases in bioinformatics
   Database types, usage, file formats, NCBI, UniProt, Protein DataBase
5. Pairwise alignments
   Edit distance, substitution matrix, significance of score, exhaustive/heuristic, global/local
6. Multiple alignments
   Dynamic programming, progressive algorithm, scoring
7. Phylogenetics
   Phylogenetic tree, terms, representation, tree-building methods
8. Profile-based methods
   Multiple alignments in practice, regular expressions, Hidden Markov Models
9. Similarity search
   Principles, heuristic search, FASTA, BLAST
10. The protein universe
    Classification, protein groups, ranking based methods, class-annotated databases, clustering
11. Next-generation sequencing
    Common aspects, steps of NGS, data store and analysis

Practical sessions

• Introduction to Perl and Python
• Programming Modules for bioinformatics
• Dynamic programming
• Software in bioinformatics: ClustalW, hmmer, JalView, BLAST, Phylip
• Introduction to database searching
• Algorithm Practice: Clustering, UPGMA