by Philip M R Tedder, James R Bradford, Chris J Needham, Glenn a McConkey, Andrew J Bulpitt, David R Westhead
Abstract:
Functional genomics data provides a rich source of information that can be used in the annotation of the thousands of genes of unknown function found in most sequenced genomes. However, previous gene function prediction programs are mostly produced for relatively well-annotated organisms that often have a large amount of functional genomics data. Here, we present a novel method for predicting gene function that uses clustering of genes by semantic similarity, a naïve Bayes classifier and 'enrichment analysis' to predict gene function for a genome that is less well annotated but does has a severe effect on human health, that of the malaria parasite Plasmodium falciparum.
Reference:
Gene function prediction using semantic similarity clustering and enrichment analysis in the malaria parasite Plasmodium falciparum. (Philip M R Tedder, James R Bradford, Chris J Needham, Glenn a McConkey, Andrew J Bulpitt, David R Westhead), In Bioinformatics (Oxford, England), volume 26, 2010.
Bibtex Entry:
@article{Tedder2010,
abstract = {Functional genomics data provides a rich source of information that can be used in the annotation of the thousands of genes of unknown function found in most sequenced genomes. However, previous gene function prediction programs are mostly produced for relatively well-annotated organisms that often have a large amount of functional genomics data. Here, we present a novel method for predicting gene function that uses clustering of genes by semantic similarity, a na\"{\i}ve Bayes classifier and 'enrichment analysis' to predict gene function for a genome that is less well annotated but does has a severe effect on human health, that of the malaria parasite Plasmodium falciparum.},
author = {Tedder, Philip M R and Bradford, James R and Needham, Chris J and McConkey, Glenn a and Bulpitt, Andrew J and Westhead, David R},
doi = {10.1093/bioinformatics/btq450},
issn = {1367-4811},
journal = {Bioinformatics (Oxford, England)},
keywords = {Cluster Analysis,Computational Biology,Computational Biology: methods,Genome, Protozoan,Genomics,Genomics: methods,Plasmodium falciparum,Plasmodium falciparum: genetics,Protozoan Proteins,Protozoan Proteins: genetics,SML-LIB-BIBLIO,lang:ENG},
mendeley-tags = {SML-LIB-BIBLIO,lang:ENG},
month = oct,
number = {19},
pages = {2431--7},
pmid = {20693320},
title = {{Gene function prediction using semantic similarity clustering and enrichment analysis in the malaria parasite Plasmodium falciparum.}},
url = {http://www.ncbi.nlm.nih.gov/pubmed/20693320},
volume = {26},
year = {2010}
}