BIOINFORMATICS

The course is intended to introduce the students to Bioinformatics, whose aim is to give computational solutions to problems in the field of molecular biology and genetics.
In particular, problems and solutions for the analysis of biological sequences, such as DNA and proteins, are considered.
In the context of Systems Biology, some examples of biological systems will be illustrated, represented with models and tools typical of computer science.

Knowledge and understanding.

The student will have mastered specific scientific terminology.
She will have acquired an introduction to bioinformatics and will have understood its potential and complexity.
She will be able to recognize and understand the IT solutions to the biological problems treated.


Ability to apply knowledge and understanding.

The student will be able to carry out exercises aimed at applying the knowledge acquired in the various topics of the course.
She will be able to perform, if required, a small software project for the solution of a biological problem.

Knowledge about algorithms and computational complexity.

The following list of topics is reduntant: only a subset, which can change from year to year, will be developed during the course.
- Introduction to molecular biology: DNA, RNA, proteins, cell.
- Sequences comparison: Pattern matching; Suffix tree; Suffix array; Pair alignment; Multiple alignment.
- Phylogenetic trees: inference and comparison.
- Genomic sequencing: technologies and strategies.
- Systems Biology: general introduction and examples.
- Metabolism: representation, analysis and comparison of metabolic networks.
- Sequences modelling: weighted and probabilistic HMM.
- Protein modelling, folding and comparison.

The course does not adopt a specific textbook but refers to the following reference books for the various topics:
- T.H. Cormen, C. E. Leiserson, R. L. Rivest, C. Stein, Introduction to Algorithm (II ed.), The MIT Press, 2001
- D. Gusfield, Algorithms on Strings, trees, and sequences, Cambridge University Press, 1997
- R. Durbin, S. Eddy, A. Krogh, G. Mitchison, Biological sequence analysis, Probabilistic models and nucleic acids, Cambridge University Press, 2002.
- D. W. Mount, Bioinformatics-Sequence and genome analysis
The teacher moreover provides the projected slides and specific papers on the various topics of the course.

The course requires a 2-hours written test and an oral test to verify the knowledge acquired.
The written text includes a series of open questions to be answered and exercises to be solved/developed on the course topics.
The oral test consists in the presentation of an scientific paper or a series of questions on the topics of the course.

The exam score is 30 points in total and is divided as follows: 10-12% of the score is assigned for the oral test, while 88-90% of the score is assigned for the written test.

written and oral

The course uses classical frontal teaching

English

Further info available at
http://moodle.unive.it