GENE0448-2

Duration

20h Th, 30h Mon. WS

Number of credits

	Master in bio-informatics and modelling (120 ECTS)	5 crédits

Lecturer

Denis Baurain

Language(s) of instruction

French language

Organisation and examination

Teaching in the first semester, review in January

Units courses prerequisite and corequisite

Prerequisite or corequisite units are presented within each program

Learning unit contents

This course aims to provide the theoretical and practical bases of phylogenetic methodology.

Reminder on (molecular) phylogenetics
Sequence alignment - global alignment (NW), local alignment (SW, BLAST), multiple alignment (ClustalW) and profiles
Parsimony - phylogenetic trees, tree length (Fitch's algorithm) and search heuristics
Distance methods - distance matrices, W(U)PGMA, NJ and models of sequence evolution
Probabilistic methods - likelihood (principle, algorithms, models, advantages and model selection), statistical support and congruence, Bayesian inference (principle and algorithms), relaxed molecular clocks
Phylogenomics - principle, stochastic and systematic errors, supertrees, supermatrices, CAT model, applications

Learning outcomes of the learning unit

Theory: At the end of this course, students will be able to explain the main concepts, methods and algorithms used in phylogenetics. They will have an intuitive understanding of probabilistic methods and will be able to justify their preferential use over other approaches. This requires, above all, to have UNDERSTOOD the course material. In this sense, this course is probably different from some other subjects of the curriculum in biology, in which mere memorization may be enough to pass the examination.
Exercises: For some algorithms (specified in class), an APPLICATION using pen and paper to solve a toy example may be requested.
Applications: The practical analysis of a dataset in a phylogenetic context will have been covered during computer practicals. Students will thus be able to concretely reproduce it on their own datasets;
Applications: The 5-credit declination of this course imposes the student to carry out a quite extensive personal project. This will help him/her to acquire a better mastery of the concepts and of the practical aspects of the phylogenetic analysis (beyond the tools covered during the computer practicals).

Prerequisite knowledge and skills

The course assumes no prerequisites in computer science, but relies on a basic knowledge of mathematics and molecular genetics. In principle, the necessary level in both subjects is reached at the end of the 3rd year of BA in biology.

Planned learning activities and teaching methods

Theoretical lectures, demonstrations and supervised exercises: 8 x 2h30.
Computer practicals (Seaview and R): 4 x 4h.
Personal project with written report (full phylogenetic study on a topic to be determined).

Mode of delivery (face-to-face ; distance-learning)

This is a face-to-face course. Attending the lectures is strongly encouraged as they are designed so as to facilitate understanding and assimilation of the course material. The personal project will be organized as an individual coaching.

Assessment methods and criteria

Evaluation has two parts:

40% : written examination (January session) including three theory questions (free-form explanation of a theoretical concept) and one exercise (algorithm to be applied);
15% : computer practical examination (at the end of the course) where one has to analyze a new dataset;
45% : written report on the personal project.

Work placement(s)

Organizational remarks

Taking notes on a laptop or tablet is allowed. However, students are expected not to surf or chat in the classroom.

Contacts

Prof. Denis Baurain Institut de Botanique B22 (P70) denis.baurain@ulg.ac.be Assistant: Dr. Damien Sirjacobs Institut de Botanique B22 (P70) 04/366.38.54 D.Sirjacobs@ulg.ac.be

Phylogenetic methods