Bioinformatics : DNA and protein sequences

lbrmc2201  2018-2019  Louvain-la-Neuve

Bioinformatics : DNA and protein sequences
4 credits
30.0 h + 15.0 h
Q1
Teacher(s)
Ghislain Michel coordinator; Mahillon Jacques;
Language
French
Prerequisites
Introductory courses in biochemistry and molecular biology
Main themes
Bioinformatics refers to a set of concepts and tools that are required for the analysis of biological data and the interpretation of the results. This introductory course focuses on molecular biology databases (DNA and protein sequences), the algorithmic bases of the sequence analysis programs and on alignment score statistics. The course identifies the many pitfalls of interpreting data by giving a critical appraisal of the softwares used for sequence analysis.
Aims

At the end of this learning unit, the student is able to :

1

a. Contribution de l¿activité au référentiel AA (AA du programme)

Cohérence des AA cours en regard de ceux du programme

1.1, 1.2, 1.3

3.1, 3.2, 3.4, 3.5, 3.6

b. Formulation spécifique pour cette activité des AA du programme (maximum 10)

At the end of this course, students will be able to perform a comprehensive and exhaustive sequence analysis, using appropriate computational programs tools and internet resources. This ability requires:

- The understanding of the algorithmic bases of the computational programs

- The description of the various molecular databases with emphasis on the positive and negative aspects of data structure and search tools

- The discussion of the prediction results and eventually the proposition of a more appropriate analysis method

-A strategy for protein function forecasting

 

The contribution of this Teaching Unit to the development and command of the skills and learning outcomes of the programme(s) can be accessed at the end of this sheet, in the section entitled “Programmes/courses offering this Teaching Unit”.
Content
1.     Overview of basic concepts in nucleic acids sequencing
2.     Sequence and 3-D structure databases, protein motif and family databases
3.     Database search tools
4.     Sequence comparison : dot plot, global and local alignment based on a dynamic programming method and score matrices
5.     Database searching for similar sequences (matching word-based method), score statistics 
6.     Multiple sequence alignment, motif discovery,(patterns, profiles, Hidden Markov models)
7.     Analysis of protein hydropathy and prediction of RNA secondary structure
8. Phylogenetic inference using phenetic and cladistic methods
Teaching methods
The theoretical part consists of ex cathedra speeches in a classroom (30h).  The training sessions (15h) consist of a set of problems to be resolved individually or by a group of 2 students, using free sequence analysis programs.
Evaluation methods
Written examination in an open-book format, including theory questions and a sequence to be analysed using the computer programs discussed in the classroom.. Criteria used are:
 - the understanding of the algorithmic bases of the sequence analysis programs
 - the use of the most appropriate program and database
- the explanation of the statistical bases of prediction scores
Biological background, concise nature and clarity of the search are also required.
Other information
This course can be given in English.
Online resources
Moodle
Bibliography
  • Bioinformatics sequence and genome analysis D. Mount
  • Bioinformatique: cours et cas pratique G. Deléage et M. Gouy
Des copies papier des diaporamas et le manuel pour les exercices sont disponibles sur Moodle.
Le cours ne fait appel à aucun support particulier qui serait payant et jugé obligatoire. L'ouvrage Bioinformatics de Mount (CSHL press) est conseillé pour un apprentissage plus approfondi
Teaching materials
  • Bioinformatics sequence and genome analysis D. Mount
  • Bioinformatique: cours et cas pratique G. Deléage et M. Gouy
Faculty or entity
AGRO


Programmes / formations proposant cette unité d'enseignement (UE)

Title of the programme
Sigle
Credits
Prerequisites
Aims
Master [120] in Agricultural Bioengineering

Master [120] in Chemistry and Bioindustries

Master [120] in Statistic: Biostatistics

Master [120] in Biochemistry and Molecular and Cell Biology

Master [60] in Biology