M1 - Eco-Epidemiology

"General linear models with 1 or more explanatory random variables: from translating the figure that answers the biological question to the statistical model, i.e., taking into account many effects and knowing how to interpret them

general properties seen through regression and 1-factor ANOVA (R2, F, ddl, least squares, likelihood, diagnosis, validation, goodness of fit, interpretation of effect sizes); nested and cross-factor ANOVA, multiple regression (notion of parameter and effects, and interaction)

incorporation of the dependence of explanatory random variables, confounding of effects (quantitative for multiple regression, and unbalanced designs for ANOVA)".

See full page

See full page

The objective of this course is to provide the necessary basis in statistics to follow all the more elaborate modules of the curriculum, so it is a general refresher. Descriptive statistics are reviewed (quantile, polygon of cumulative frequencies, estimators from samples), simple tests are presented, essential graphs for univariate and multivariate data are presented, the general principle of a statistical test, the hypothesis plan, the notion of p-value, first and second species risk are presented. In practical exercises, students are also brought up to speed in the R environment.

See full page

See full page

See full page

This course is conducted entirely in English. Its objective is twofold: 

1. To enable students to improve their oral expression and comprehension in English 

2. To allow students to enrich their vocabulary in the field of ecology that interests them most (e.g. marine ecology, terrestrial ecology).  

Practical work: oral presentations made by students, listening to videos in English with English subtitles, quizzes, games.   

See full page

See full page

"The phylogenetic tree is a central concept in biology for students in the fields of ""Biodiversity, Ecology & Evolution"", ""Biology Agrosciences"", and ""Eco-epidemiology"". To approach phylogeny, this UE is divided into two successive parts of 22,5h each: ""Phylogeny and Evolution (Basics)"" (HAB708B) and ""Phylogeny and Evolution (Advanced)"" (HAB714B).

The following knowledge will be taught:

(i) History of the notion of evolution [Basics].

(ii) Phylogenetic systematics (characters, rules of taxonomy, molecular barcoding, genomics, alignment, homology and homoplasy, orthology and paralogy) [half in Basic; half in Advanced].

(iii) Phylogenetic representation (networks, trees, root, dendrograms, topology, branch lengths) [Bases].

(iv) Phylogenetic inference methods by distances [Advanced].

(v) The cladistic approach and the maximum parsimony principle [Basics].

(vi) The probabilistic approach, the maximum likelihood principle, and sequence evolution models [Advanced].

(vii) Measures of phylogeny robustness (bootstrap, topology comparison, multigene corroboration, gene and species trees) [Advances].

(viii) Applications to the phylogeny of some major taxonomic groups (Mammals, Eukaryotes) [Advances]."

See full page

See full page

See full page

See full page

See full page

See full page

See full page

See full page

See full page

See full page

See full page

See full page

See full page

See full page

This EU has three objectives:

1) deepen knowledge of concepts in genetics and evolutionary genomics such as linkage disequilibrium, selection, coalescent theory, detection of natural selection and evolutionary forces acting on genome evolution and the process of genomic speciation.

2) To propose a panorama of research themes in evolutionary genomics in the form of pedagogical seminars: molecular evolution, evolutionary genomics of endosymbioses, chromosomal evolution and molecular evolution.

3) Finally, the EU proposes a project of bioanalysis of an empirical dataset to understand the analysis in evolutionary genomics and to rub shoulders with the bioinformatics aspects increasingly developed in the discipline.

See full page

"The objective of this course is to complete the first semester's teaching by developing the problems related to the evolution of phenotypes and the main associated methodological approaches. The lectures will address the evolution of different types of traits (life history traits, traits involved in reproductive strategies, traits involved in biotic interactions, quantitative traits). The main approaches covered include game theory formalization, adaptive dynamics, quantitative genetic approaches, and the work of confronting theoretical predictions with empirical data. Coursework includes:

1) lectures on the main concepts of evolutionary ecology;

2) tutorials focused on document studies and exercises".

See full page

"This module presents table management and the link between multivariate and univariate: matrix manipulation and common operations; notion of projection and distance; translation of descriptive and univariate statistics with multiple regression/ACP/AFD as an example; (dis)similarity indices, distance; correlation"

See full page

See full page

See full page

See full page

See full page

See full page

See full page

See full page

See full page