Abstract: Plasmodium falciparum is the parasite responsible for more than
90% of deaths that occur due to malaria. Organization and mining of 'omic'
(genomic, proteomic, transcriptomic, interactomic) data can improve our
understanding of P. falciparum biology and help in the fight against
malaria. PlasmoID (Plasmodium Information Discovery) is a tool developed for
the dynamic exploration of the parasite's 'omic' landscape. Diverse
computational and curated P. falciparum protein-protein interaction
datasets, as well as binary relationships involving protein-small molecule
entities, manually curated protein-protein relationships derived from the
published literature and protein-protein interactions based on metabolic
pathways are included in the PlasmoID database. The graphical user interface is
designed as a plug-in to Cytoscape, an open-source network visualization tool.
Important features of this plug-in include a synchronized tabular
representation of any network loaded on the canvas, ability to find the
shortest path between a pair of nodes in the database, search and expansion of
entities from the database, and the ability to add new entities to the database
through the interface. Malaria researchers can now seamlessly interrogate
heterogeneous 'omic' datasets as well as add proprietary data to generate and
visualize P. falciparum pathway and cell process network models. PlasmoID
can be downloaded from http://pfalciparum.atc.tcs.com/PlasmoID.
Keywords: P. falciparum, malaria, systems biology, PlasmoID, interactome
