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Life Sciences
Participants : Amedeo Napoli
Bernard Maigret
Dave Ritchie
Elias Egho
Emmanuel Bresso
Lazaros Mavridis
Malika Smaïl-Tabbone
Marie-Dominique Devignes
Nicolas Jay
Renaud Grisoni
Sid-Ahmed Benabderrahmane
Thomas Bourquard
Violeta Pérez-Nueno
Vishwesh Venkatraman
Yannick Toussaint
Yasmine Asses

Knowledge discovery in life sciences 
It is a process for extracting knowledge units from large biological databases, e.g. collection of genes.

One major application domain which is currently investigated by Orpailleur team is related to life sciences, with particular emphasis on biology, medicine, and chemistry. The understanding of biological systems provides complex problems for computer scientists, and, when they exist, solutions bring new research ideas for biologists and for computer scientists as well. Accordingly, the Orpailleur team includes biologists, chemists, and a physician, making Orpailleur a very original EPI at INRIA.

Knowledge discovery is gaining more and more interest and importance in life sciences for mining either homogeneous databases such as protein sequences and structures, or heterogeneous databases for discovering interactions between genes and environment, or between genetic and phenotypic data, especially for public health and pharmacogenomics domains. The latter case appears to be one main challenge in knowledge discovery in biology and involves knowledge discovery from complex data and thus KDDK. The interactions between researchers in biology and researchers in computer science improve not only knowledge about systems in biology, chemistry, and medicine, but knowledge about computer science as well. Solving problems for biologists using KDDK methods involves the design of specific modules that, in turn, leads to adaptations of the KDDK process, especially in the preparation of data and in the interpretation of the extracted units.