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Malaria Journal 5, 1 (2006) 110
Integration and mining of malaria molecular, functional and pharmacological data: how far are we from a chemogenomic knowledge space?
Lyn-Marie Birkholtz1, Olivier Bastien2, Gordon Wells3, Delphine Grando4, Fourie Joubert3, Vinod Kasam5, Marc Zimmermann6, Philippe Ortet7, Nicolas Jacq5, Nadia Saïdani4, 8, Sylvaine Roy9, Martin Hofmann-Apitius6, Vincent Breton5, Abraham I Louw1, Eric Maréchal4

The organization and mining of malaria genomic and post-genomic data is important to significantly increase the knowledge of the biology of its causative agents, and is motivated, on a longer term, by the necessity to predict and characterize new biological targets and new drugs. Biological targets are sought in a biological space designed from the genomic data from Plasmodium falciparum, but using also the millions of genomic data from other species. Drug candidates are sought in a chemical space containing the millions of small molecules stored in public and private chemolibraries. Data management should, therefore, be as reliable and versatile as possible. In this context, five aspects of the organization and mining of malaria genomic and post-genomic data were examined: 1) the comparison of protein sequences including compositionally atypical malaria sequences, 2) the high throughput reconstruction of molecular phylogenies, 3) the representation of biological processes, particularly metabolic pathways, 4) the versatile methods to integrate genomic data, biological representations and functional profiling obtained from X-omic experiments after drug treatments and 5) the determination and prediction of protein structures and their molecular docking with drug candidate structures. Recent progress towards a grid-enabled chemogenomic knowledge space is discussed.
1 :  African Centre for Gene Technologies
2 :  LAPM - Laboratoire Adaptation et pathogénie des micro-organismes
3 :  Bioinformatics and Computational Biology Unit
4 :  LPCV - Laboratoire de physiologie cellulaire végétale
5 :  LPC - Laboratoire de Physique Corpusculaire [Clermont-Ferrand]
6 :  Fraunhofer Institute for Algorithms and Scientific Computing
7 :  Département d'Ecophysiologie Végétale et de Microbiologie
8 :  DMIM - Dynamique moléculaire des interactions membranaires
9 :  LBIM - Laboratoire Biologie-Informatique-Mathématique

Sciences du Vivant/Biochimie, Biologie Moléculaire
malaria – Plasmodium falciparum – genome – data mining – protein sequence comparison – molecular phylogeny – metabolic pathway – protein structure prediction – drug target – chemogenomics – statistics
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