Probabilistic annotation of protein sequences based on functional classifications
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* Corresponding authors: Christos A Ouzounis ouzounis@ebi.ac.uk - Benjamin Audit Benjamin.Audit@ens-lyon.fr
BMC Bioinformatics 2005, 6:302 doi:10.1186/1471-2105-6-302
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Sequence-based feature prediction and annotation of proteins Agnieszka S Juncker, Lars J Jensen, Andrea Pierleoni, Andreas Bernsel, Michael L Tress, Peer Bork, Gunnar von Heijne, Alfonso Valencia, Christos A Ouzounis, Rita Casadio, Søren Brunak Genome Biology 2009, 10:206 (2 February 2009) This article is part of a collection on BioSapiens The combination of prediction tools in complex workflows and pipelines facilitates prediction of protein features from sequence. |
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Towards a semi-automatic functional annotation tool based on decision-tree techniques Jérôme Azé, Lucie Gentils, Claire Toffano-Nioche, Valentin Loux, Jean-François Gibrat, Philippe Bessières, Céline Rouveirol, Anne Poupon, Christine Froidevaux BMC Proceedings 2008, 2(Suppl 4):S3 (17 December 2008) |
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ProbCD: enrichment analysis accounting for categorization uncertainty Ricardo ZN Vêncio, Ilya Shmulevich BMC Bioinformatics 2007, 8:383 (12 October 2007) |
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Exploring inconsistencies in genome-wide protein function annotations: a machine learning approach Carson Andorf, Drena Dobbs, Vasant Honavar BMC Bioinformatics 2007, 8:284 (3 August 2007) |
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Applying negative rule mining to improve genome annotation Irena I Artamonova, Goar Frishman, Dmitrij Frishman BMC Bioinformatics 2007, 8:261 (21 July 2007) |
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CORRIE: enzyme sequence annotation with confidence estimates Benjamin Audit, Emmanuel D Levy, Wally R Gilks, Leon Goldovsky, Christos A Ouzounis BMC Bioinformatics 2007, 8(Suppl 4):S3 (22 May 2007) |
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The 2006 Automated Function Prediction Meeting Ana PC Rodrigues, Barry J Grant, Adam Godzik, Iddo Friedberg BMC Bioinformatics 2007, 8(Suppl 4):S1 (22 May 2007) |
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Nandini Krishnamurthy, Duncan P Brown, Dan Kirshner, Kimmen Sjölander Genome Biology 2006, 7:R83 (14 September 2006) PhyloFacts, a structural phylogenomic database for protein functional and structural classification, is described. |
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BayGO: Bayesian analysis of ontology term enrichment in microarray data Ricardo ZN Vêncio, Tie Koide, Suely L Gomes, Carlos A de B Pereira BMC Bioinformatics 2006, 7:86 (23 February 2006) Searching for enriched ontology terms in microarray data is improved by an innovative, freely available Bayesian approach that accounts for genes missed in the analysis, offering an advance on 'frequentist' approaches.
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