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This article is part of the supplement: Quantitative inference of gene function from diverse large-scale datasets

Open AccessMethod

Consistent probabilistic outputs for protein function prediction

Guillaume Obozinski1, Gert Lanckriet2, Charles Grant3, Michael I Jordan4 and William Stafford Noble5 email

1Department 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

author email corresponding author email

Genome Biology 2008, 9(Suppl 1):S6doi:10.1186/gb-2008-9-s1-s6

Published: 27 June 2008

Additional files

Additional 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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