<> "The repository administrator has not yet configured an RDF license."^^ . <> . . "Integration and analysis of large scale data in chemical biology"^^ . "much lower molecular weight than macromolecules like proteins or DNA. Small molecules are grouped into different\r\nfamilies according to their physico-chemical or functional properties, and they can be either natural (like lipids) or\r\nsynthetic (like drugs). Only a staggeringly low fraction of the small molecule universe has been characterize, and\r\nvery little is known about it. For instance, we know that lipids can play the role of scaffolding and energy storage\r\ncompounds, and that they differently compose biological membranes. However, we don’t know if it influences some\r\nbiological functions, including protein recruitment to membranes and cellular transport.\r\nChemical biology aims at utilizing chemicals in order to explore biological systems. Advances in synthesizing big\r\nchemical libraries as well as in high-throughput screenings have led to technologies capable of studying protein-lipid\r\ninteractions at large scale and in physiological conditions. Therefore, answering such questions has become possible, but\r\nit presents many new computational challenges. For instance, establishing methods capable of automatically classifying\r\ninteractions as binding or non-binding requiring a minimal interaction with human experts. Making use of unsupervised\r\nclustering methods to identify clusters of lipids and proteins exhibiting similar patterns and linking them to similar\r\nbiological functions.\r\nTo tackle these challenges, I have developed a computational pipeline performing a technical and functional analysis\r\non the readouts produced by the high-throughput technology LiMA. Applied to a screen focusing on 94 proteins and 122\r\nlipid combinations yielding more than 10,000 interactions, I have demonstrated that cooperativity was a key mechanism\r\nfor membrane recruitment and that it could be applied to most PH domains. Furthermore, I have identified a conserved\r\nmotif conferring PH domains the ability to be recruited to organellar membranes and which is linked to cellular transport\r\nfunctions. Two amino acids of this motif are found mutated in some human cancer, and we predicted and confirmed\r\nthat these mutations could induce discrete changes in binding affinities in vitro and protein mis-localization in vivo.\r\nThese results represent milestones in the field of protein-lipid interactions.\r\nWhile we are progressing toward a global understanding of protein-lipid interactions, data on the bioactivities of\r\nsmall molecules is accumulating at a tremendous speed. In vitro data on interactions with targets are complemented\r\nby other molecular and phenotypic readouts, such as gene expression profiles or toxicity readouts. The diversity\r\nof screening technologies accompanied by big efforts to collect the resulting data in public databases have created\r\nunprecedented opportunities for chemo-informatics work to integrate these data and make new inferences. For instance,\r\nis the protein target profile of a drug correlated with a given phenotype? Can we predict the side effects of a drug\r\nbased on its toxicology readouts? In this context, I have developed CART: a computational platform with which\r\nwe address major chemo-informatics challenges to answer such questions. CART integrates many resources covering\r\nmolecular and phenotypical readouts, and annotates sets of chemical names with these integrated resources. CART\r\nincludes state-of-the-art full-text search engine technologies in order to match chemical names at a very high speed\r\nand accuracy. Importantly, CART is a scalable resource that can cope with the increasing number of new chemical\r\nannotation resources, and therefore, constitutes a major contribution to chemical biology."^^ . "2016" . . . . . . . "Samy Lyes"^^ . "Deghou"^^ . "Samy Lyes Deghou"^^ . . . . . . "Integration and analysis of large scale data in chemical biology (PDF)"^^ . . . "SLD_PhD_Thesis.pdf"^^ . . . "Integration and analysis of large scale data in chemical biology (Other)"^^ . . . . . . "lightbox.jpg"^^ . . . "Integration and analysis of large scale data in chemical biology (Other)"^^ . . . . . . "preview.jpg"^^ . . . "Integration and analysis of large scale data in chemical biology (Other)"^^ . . . . . . "medium.jpg"^^ . . . "Integration and analysis of large scale data in chemical biology (Other)"^^ . . . . . . "small.jpg"^^ . . . "Integration and analysis of large scale data in chemical biology (Other)"^^ . . . . . . "indexcodes.txt"^^ . . "HTML Summary of #19266 \n\nIntegration and analysis of large scale data in chemical biology\n\n" . "text/html" . . . "000 Allgemeines, Wissenschaft, Informatik"@de . "000 Generalities, Science"@en . .