BACKGROUND: Of the 5,484 predicted proteins of Plasmodium falciparum, the main 
causative agent of malaria, about 60% do not have sufficient sequence similarity 
with proteins in other organisms to warrant provision of functional assignments. 
Non-homology methods are thus needed to obtain functional clues for these 
uncharacterized genes.
RESULTS: We present PlasmoDraft http://atgc.lirmm.fr/PlasmoDraft/, a database of 
Gene Ontology (GO) annotation predictions for P. falciparum genes based on 
postgenomic data. Predictions of PlasmoDraft are achieved with a Guilt By 
Association method named Gonna. This involves (1) a predictor that proposes GO 
annotations for a gene based on the similarity of its profile (measured with 
transcriptome, proteome or interactome data) with genes already annotated by 
GeneDB; (2) a procedure that estimates the confidence of the predictions 
achieved with each data source; (3) a procedure that combines all data sources 
to provide a global summary and confidence estimate of the predictions. Gonna 
has been applied to all P. falciparum genes using most publicly available 
transcriptome, proteome and interactome data sources. Gonna provides predictions 
for numerous genes without any annotations. For example, 2,434 genes without any 
annotations in the Biological Process ontology are associated with specific GO 
terms (e.g. Rosetting, Antigenic variation), and among these, 841 have 
confidence values above 50%. In the Cellular Component and Molecular Function 
ontologies, 1,905 and 1,540 uncharacterized genes are associated with specific 
GO terms, respectively (740 and 329 with confidence value above 50%).
CONCLUSION: All predictions along with their confidence values have been 
compiled in PlasmoDraft, which thus provides an extensive database of GO 
annotation predictions that can be achieved with these data sources. The 
database can be accessed in different ways. A global view allows for a quick 
inspection of the GO terms that are predicted with high confidence, depending on 
the various data sources. A gene view and a GO term view allow for the search of 
potential GO terms attached to a given gene, and genes that potentially belong 
to a given GO term.