Biological Data Integration: Computer and Statistical Approaches

The study of biological data is constantly undergoing profound changes. Firstly, the volume of data available has increased considerably due to new high throughput techniques used for experiments. Secondly, the remarkable progress in both computational and statistical analysis methods and infrastructures has made it possible to process these voluminous data.

The resulting challenge concerns our ability to integrate these data, i.e. to use their complementary nature effectively in the hope of advancing our knowledge. Therefore, a major challenge in studying biology today is integrating data for the most exhaustive analysis possible.

Biological Data Integration deals in a pedagogical way with research work in biological data science, examining both computational approaches to data integration and statistical approaches to the integration of omics data.

Christine Froidevaux is Professor Emeritus of Computer Science at the Université Paris-Saclay, France, and her research focuses on data integration for biological systems.

Marie-Laure Martin-Magniette is Research Director at INRAE, France, where she develops statistical methodologies for analyzing and integrating omics data.

Guillem Rigaill is Research Director at INRAE, France, where he develops statistical methodologies for (multi)omics analysis.