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By Rachel Karchin, Alvaro N. A. Monteiro, Sean V. Tavtigian, Marcelo A. Carvalho and Andrej SaliRachel Karchin and Andrej Sali

Abstract

This is a provisional PDF of the author-produced electronic version of a manuscript that has been accepted for publication. Although this article has been peer-reviewed, it was posted immediately upon acceptance and has not been copyedited, formatted, or proofread. Feel free to download, use, distribute, reproduce, and cite this provisional manuscript, but please be aware that there will be significant differences between the provisional version and the final published version. Provisional doi:10.1371/journal.pcbi.0030026.eor Copyright: © 2007 Karchin et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Citation: Karchin R, Monteiro AN, Tavtigian SV, Carvalho MA, Sali A (2007) Functional impact of missense variants in BRCA1 predicted by supervised learning. doi:10.1371/journal.pcbi.0030026.eor Future Articl

Topics: Running head, Predicting the impact of missense variants Keywords, BRCA1, unclassified variant, breast cancer, machine learning, naïve Bayes, support vector machine, random forest, decision tree, missense mutation, protein structure prediction Abbreviations, BR
Year: 2009
DOI identifier: 10.1371/journal.pcbi.0030026.eor
OAI identifier: oai:CiteSeerX.psu:10.1.1.135.3245
Provided by: CiteSeerX
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