Algorithms and programming languages for bioinformatics (2011/2012)

  1. Home
  2. Teaching
  3. Master's degrees
  4. Master's degree in Bioinformatics and Medical Biotechnology
  5. Insegnamenti

Course not running

Course code
4S000525
Credits
12
Coordinator
Zsuzsanna Liptak
Course news Seminars related to the course
Teaching is organised as follows:
Unit Credits Academic sector Period Academic staff
LINGUAGGI PER BIOINFORMATICA 6 INF/01-INFORMATICS See the unit page See the unit page
ALGORITMI PER BIOINFORMATICA 6 INF/01-INFORMATICS II semestre Zsuzsanna Liptak

Learning outcomes

Module: LINGUAGGI PER BIOINFORMATICA
-------



Module: ALGORITMI PER BIOINFORMATICA
-------
1. to learn about some basic problems and algorithms behind common bioinformatics applications (alignment, sequence similarity, phylogenetics), and 2. to get an idea of some basic computational issues (complexity, efficiency, limitations).

Syllabus

Module: LINGUAGGI PER BIOINFORMATICA
-------



Module: ALGORITMI PER BIOINFORMATICA
-------
SEQUENCE ALIGNMENT

Applications; Pairwise sequence alignment: Exhaustive search, Dynamic programming (DP) algorithm of Needleman-Wunsch (global alignment), DP algorithm of Smith-Waterman (local alignment), other variants (sketch); Formalism on strings/sequences; Scoring matrices: PAM (computation, application); Heuristics for sequence alignment: dotplots, q-grams, FASTA, BLAST;

STRING SIMILARITY AND DISTANCE

String similarity and distance: percent similarity, edit distance, Hamming distance, connection between edit distance and alignment score;

ALGORITHM ANALYSIS

Introduction to algorithm analysis: time and storage space analysis; notation for complexity analysis: Big-Oh-notation, growth of functions;

PHYLOGENETICS

History of systematics; Introduction to graphs and trees; number of phylogenetic trees; distance-based data: UPGMA; character-based data: Perfect Phylogeny (PP), Small parsimony: Fitch' algorithm; Large parsimony: heuristics (sketch);

STATISTICS

Some basic statistics (hypothesis testing, P-values, type I and II errors, descriptive statistics).

Assessment methods and criteria

Module: LINGUAGGI PER BIOINFORMATICA
-------



Module: ALGORITMI PER BIOINFORMATICA
-------
Written exam: 50%, and presentation of a project (talk with digital slides): 50%
The written exam can be taken in two parts (midterm and final), in which case both have to be passed; or in one (complete final exam).

Share