Biological data modeling

This course is a natural continuation of the course " Quantification of Risk " (HAV424B) presented in S4. It aims to provide the concepts for constructing experimental protocols that answer biological questions and to associate them with appropriate models for analyzing variability. The first part will be devoted to the construction of experimental protocols that can answer a multitude of questions in the life sciences, i.e., taking into account the inevitable dependence of statistical individuals, such as kinship, spatial or temporal structure of populations. This part will provide an opportunity to address the concepts of fluctuation, replication, and pseudo-replication, which will be taken into account in the models constructed in the second part of the course. The second part will focus on demonstrating the link between the experimental protocol carried out and the modeling of the variability of a quantitative response variable, through the construction of models including several qualitative or quantitative variables. Particular attention will be paid to the conditions for applying these methods, type I and II errors, methods for estimating the parameters of the models constructed (including likelihood), and the interpretation of the estimated parameters. Each concept will be illustrated by the analysis of real biological data from several topics, helping students to discover not only modern and current biological issues but also the tools developed to address them. Practical work using R will enable students to independently perform analyses on published biological cases.

- HAV312B, HAV313B, and HAV424B

- Use mathematical tools to build statistical models of variability and address issues in the life sciences.

- adjust the protocol to the question asked

- adjust a model to experimental data

- validate a model's predictions and assess its limitations