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GO-At: In silico prediction of gene function in Arabidopsis thaliana by combining heterogeneous data

<28>Due to bottlenecks of sparse and disparate data, previous gene function prediction attempts were restricted to well annotated genomes or predicted only one functional aspect, hindering progress. Integrating data sources and using the Gene Ontology (http://www.geneontology.org/), our classification method was the first to both identify associated genes and predict multiple gene functions. Our valuable web-tool http://fbs3pcu112.leeds.ac.uk/goat/ provides a unique resource for plant geneticists worldwide (e.g., Verona University, doi:10.1371/journal.pone.0041327). Applications to other domains include our work within BBSRC's major Insect Pollinator Initiative (effects of land use on pollinators, BB/I000364/1, £384K). This journal ranks among the top five journals in plant science.