This article is part of the supplement: Quantitative inference of gene function from diverse large-scale datasetsConsistent probabilistic outputs for protein function prediction1Department of Statistics University of California, Berkeley, Berkeley, CA 94720, USA 2Department of Electrical and Computer Engineering, University of California, San Diego, San Diego, CA 92093, USA 3Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA 4Department of Statistics, Department of Electrical Engineering and Computer Science, University of California, Berkeley, Berkeley, CA 94720, USA 5Department of Genome Sciences, Department of Computer Science and Engineering, University of Washington, Seattle, WA 98195, USA
Genome Biology 2008, 9(Suppl 1):S6doi:10.1186/gb-2008-9-s1-s6
Additional filesAdditional data file 1: A detailed description of the 11 reconciliation methods used in this study. Format: PDF Size: 115KB Download file This file can be viewed with: Adobe Acrobat Reader Additional data file 2: A systematic set of figures summarizing the performance of all 12 methods across all three evaluation modes, four term sizes, and four recall levels. Format: PDF Size: 1.6MB Download file This file can be viewed with: Adobe Acrobat Reader |


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