PlasmoID: A Plasmodium falciparum interactome database
SystemWide-ranging annotations for gene identification, protein function, post-translational modifications and sub-cellular localization are available for the malarial parasite Plasmodium falciparum (P. falciparum). These annotations are a result of both experimental as well as in silico methods and have been integrated into a public-domain repository called PlasmoDB (http://plasmodb.org/plasmo/).A system's biology approach that studies metabolic pathways and other biological processes provides context to the various annotations and aids in understanding the underlying biology of the organism. Birkholz et al [2006] identify the main challenge in integration of P. falciparum molecular, functional and pharmacological data as designing underlying models for building graphs from genomic data, metabolite data, reaction connections and compartmentalization information for both gene products and metabolites. The difficulty of organizing molecular data into knowledge representations becomes more pronounced in the analysis of 'omic' (proteomic, transcriptomic and interactomic) datasets. PlasmoID has been designed to build metabolic pathways using protein-protein interactions (PPI) from interactome datasets as well as user defined datasets. |
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An overview of PlasmoID database schema and plugin features is provided below:
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DownloadPlease follow the installation procedure provided in the installation guide after downloading the PlasmoID archive (plasmoID.zip) and extracting it to the local folder on your computer.Tools:
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Documentation:The system requirements and technical aspects are provided in the Technical Guide. The User Guide provides a walk-through the usage of the plugin and the database.
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References(1) Birkholtz L.-M., Bastien O., Wells, G., Grando, D., Joubert, F., Kasam, V., Zimmermann, M., Ortet, P., Jacq, N., Saidani, N., Hofmann-Apitius, S., Hofmann-Apitius, M., Breton, V., Louw, A.I., Marechal, E., Integration and mining of malaria molecular, functional and pharmacological data: how far are we from a chemogenomic knowledge space?. Malaria Journal 2006, 5:110. |
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Team
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