Release 3.0 September 2003
PlasmoCyc is a Genome/Pathway database specifically developed for the eukaryotic parasite Plasmodium falciparum (3D7), which is the major causal agent of malaria worldwide. In addition to graphical representations of metabolic pathways, PlasmoCyc can display individual enzymatic reactions with the chemical structures of the substrates and reactants. PlasmoCyc contains information regarding the association of protein subunits into complexes and the predicted cellular localizations of individual gene products. Furthermore, it provides a whole-cell overview of all metabolic pathways and tools for comparing pathways between organisms.
PlasmoCyc was built using the sequence of the P. falciparum (3D7) genome (Gardner et al., 2002), sequenced in collaboration by the Sanger Centre, The Institute for Genome Research TIGR/NMRC, and the Stanford DNA Sequencing and Technology Center and downloaded from PlasmoDB (version 4.1). This data set includes the predicted protein sequences and their annotations from the Plasmodium falciparum Genome Project. In cases where PlasmoDB assigned E.C. numbers, they were used to map proteins to E.C. reactions. The annotations and E.C. numbers were used as input to PathoLogic, which built an initial version of PlasmoCyc automatically. Additional enzymes and reactions were added manually using the biological literature as a reference. A link to the PubMed abstract of the article is included for all proteins which were annotated based on the literature. Pathways inferred by PathoLogic were supplemented with Plasmodium pathways identified by Dr. Hagai Ginsburg and available on his Malaria Parasite Metabolic Pathways webpage.
A comprehensive review of every piece of literature accumulated over decades of experimental research is beyond the scope of this project. To ensure the best quality possible, we appreciate the feedback and input from malaria researchers around the world. However, we would like to remind you that PlasmoCyc is a project in progress and its usefulness and reliability will increase as time goes by.
Funding Agency and Additional Acknowledgments
This work is supported by the Burroughs Wellcome Fund.
Iwei Yeh, Stanford University
Theodor Hanekamp,
University of Wyoming
Sophia Tsoka,
European Bioinformatics Institute
Peter D. Karp, SRI International
Russ Altman, Stanford
University
We thank Hagai Ginsburg for useful discussions.
Please send email concerning the content of PlasmoCyc to:
plasmocyc@helix.stanford.edu
Please send email concerning the Pathway Tools software:
ecocyc-support@ai.sri.com
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