Introduction to Bioinformatics

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


  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