Thesaurus-based disambiguation of gene symbols

BACKGROUND: Massive text mining of the biological literature holds great promise of relating disparate information and discovering new knowledge. However, disambiguation of gene symbols is a major bottleneck. RESULTS: We developed a simple thesaurus-based disambiguation algorithm that can operate with very little training data. The thesaurus comprises the information from five human genetic databases and MeSH. The extent of the homonym problem for human gene symbols is shown to be substantial (33% of the genes in our combined thesaurus had one or more ambiguous symbols), not only because one symbol can refer to multiple genes, but also because a gene symbol can have many non-gene meanings. A test set of 52,529 Medline abstracts, containing 690 ambiguous human gene symbols taken from OMIM, was automatically generated. Overall accuracy of the disambiguation algorithm was up to 92.7% on the test set. CONCLUSION: The ambiguity of human gene symbols is substantial, not only because one symbol may denote multiple genes but particularly because many symbols have other, non-gene meanings. The proposed disambiguation approach resolves most ambiguities in our test set with high accuracy, including the important gene/not a gene decisions. The algorithm is fast and scalable, enabling gene-symbol disambiguation in massive text mining applications

Update on human genome completion and annotations: Gene nomenclature

Abstract Why is agreeing on one particular name for each gene important? As one genome after another becomes sequenced, it is imperative to consider the complexity of genes, genetic architecture, gene expression, gene-gene and gene-product interactions and evolutionary relatedness across species. To agree on a particular gene name not only makes one's own research easier, but will also be helpful to the present generation, as well as future generations, of graduate students and postdoctoral fellows who are about to enter genomics research.</p

Genew: the Human Gene Nomenclature Database, 2004 updates

Genew, the Human Gene Nomenclature Database http://www.gene.ucl.ac.uk/cgi-bin/nomenclature/searchgenes.pl is the only resource that provides data for all human genes that have approved symbols. It is managed by the HUGO Gene Nomenclature Committee (HGNC) as a confidential database, containing over 22 000 records, 75% of which are represented online by a publicly searchable text file. Since 2002, there have been significant improvements to the Genew search engine. Additionally we have increased our capacity to analyse confidential sequence data, which has enabled us to manage the large numbers of gene symbol requests that we receive from the chromosome sequencing consortia

Genetic studies of body mass index yield new insights for obesity biology

Note: A full list of authors and affiliations appears at the end of the article. Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci (P 20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis.</p