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Data Analysis Course
2023

Thursday mornings 09/07/23 to 11/23/23

A course jointly organized by ENS and Institut Pasteur on statistical analysis of biological data will be held from 7th September to 23rd November 2023 and a few places are available for PhD students from INCEPTION program.  

Summary :

Analyzing complex and large biological data has nowadays become essential to address challenging questions in Biology, ranging from genomes organisation to the functioning of ecosystems. However, students training in data sciences still lags these new requirements in Biology. Here, we propose a course jointly organized by ENS and Institut Pasteur to train students from the PSL master in Life Sciences and from the INCEPTION PhD program on statistical analysis methods, with applications to biological data. The course will be held every Thursday morning. During the course, teachers will provide an overview of data analysis methods, from univariate to multivariate approaches. Elements of statistical modeling will also be introduced as well as experimental design and power analysis. During this course, standard statistical methods will be taught by mixing analytical and practical aspects. These approaches will be illustrated with cutting-edge biological data such as proteomics, qPCR or single cell RNA-Seq data. More challenging issues will be further discussed, such as multiple testing in omics data, e.g. when significance testing of thousands of genes or proteins is required.

Pre-requisites : 

The students should have basics in R/Markdown programming and in statistics (e.g. sampling, random variables, discrete and continuous distributions, quantiles, etc).

Applications : 

The program and contacts are available on the course webpage https://www.enseignement.biologie.ens.fr/spip.php?article91

Application deadline is the 25th August.


Feel free to contact the coordinators (BenoĆ®t Perez-Lamarque benoit.perez@ens.psl.eu from ENS and Emeline Perthame emeline.perthame@pasteur.fr from Institut Pasteur) for questions and applications. 

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