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Bioinformatics Description

Key Elements

Code

BIOA 426

Formation

M1 Cellular and Molecular Biology - Section 2

Semester

2

Credits

4

Number of Teaching Hours

36

Number of Tutoring Sessions

0

Number of Laboratory Sessions

0

Content

Objective

This course introduces the scientist to Bioinformatics, which uses computer databases to store, retrieve and assist in understanding biological information. Genome-scale sequencing projects have led to an explosion of genetic sequences available for automated analysis. These gene sequences are the codes, which direct the production of proteins that in turn regulate all life processes. The student will be shown how these sequences can lead to a much fuller understanding of many biological processes allowing pharmaceutical and biotechnology companies to determine for example new drug targets or to predict if particular drugs are applicable to all patients. Students will be introduced to the basic concepts behind Bioinformatics and Computational Biology tools. Hands-on sessions will familiarize students with the details and use of the most commonly used online tools and resources. The course will cover the use of NCBI's Entrez, BLAST, PSI-BLAST, ClustalW, Pfam, PRINTS, BLOCKS, Prosite and the PDB. An introduction to database design and the principles of programming languages will be provided.

Content

1. Introduction 1.1. What is bioinformatics? 1.2. History 1.2. Basic concepts 1.2.1. Protein and amino acid 1.2.2. DNA & RNA 1.2.3. Sequence, structure and function 2. Bioinformatics databases 2.1. Introduction 2.1.1. Motivation 2.1.2. Type of databases 2.1.3. Bibliographic databases 2.2. Nucleotide sequence databases 2.2.1. EMBL 2.2.2. GeneBank 2.2.3. DDBJ 2.2.4. UniGene 2.2.5. SGD 2.2.6. Genome Biology 2.3. Protein sequence databases 2.3.1. SwissProt/TrEMBL 2.3.2. PIR 2.4. Sequence motif databases 2.4.1. Pfam 2.4.2. PROSITE 2.5. Protein structure databases 2.5.1. Protein Data Bank 2.5.2. SCOP 2.5.3. CATH 3. Sequence alignment and database searching 3.1. Single sequence alignments 3.1.1. Biological motivation 3.1.2. Pairwise alignments 3.1.2.1.Scoring matrix 3.1.2.1.1. PAM 3.1.2.1.2. BLOSUM 3.1.2.2.Gap penalty 3.1.3. Dynamics programming 3.1.3.1.Needleman-Wunsch 3.1.3.2.Smith-Waterman 3.1.4. Heuristic methods 3.1.4.1.FASTA 3.1.4.2.BLAST 3.1.5. Statistics of sequence alignment score 3.1.5.1.E-Value 3.1.5.2.P-Value 3.2. Multiple sequence alignments 3.2.1. ClustalW 3.2.2. Profile 3.2.3. PSI-BLAST 4. Phylogenetics Lab sessions Lab 1: Interrogation of bibliograpic databases, PUBMED, MESH,….. Lab2 : Nucleotide databases: EMBL, Genbank,…. Lab 3 : Protein databases, Uniprot, Motif databases : Superfamily, PFAM, Prosite Lab 4 : Dotplot, Simple pairwise alignment, FASTA at EBI and at Virginia Lab 5 : Blast :Blast at NCBI and at EBI, MEGABLAST Lab 6 : Multiple sequence alignment : ClustalW, Profile, PSI Blast, Tour of Bioinformatics Sites, Expasy, NetPhos,…… Presentation of personal project References Zvelebil M. and Baum J. (2008) Understanding Bioinformatics, Garland Science texbooks. Mount D.W. (2004) Bioinformatics: Sequences and Genome Analysis, Cold Spring Harbor Laboratory Press, 2nd ed. Claverie JM and Notredame c. (2007). Bioinformatics for DUMMIERS. WileyPublishing, Inc., 2nd ed.