NDLI: CanPredict: a computational tool for predicting cancer-associated missense mutations

Content Provider	PubMed Central
Author	Kaminker, Joshua S. Zhang, Yan Watanabe, Colin Zhang, Zemin
Copyright Year	2007
Abstract	Various cancer genome projects are underway to identify novel mutations that drive tumorigenesis. While these screens will generate large data sets, the majority of identified missense changes are likely to be innocuous passenger mutations or polymorphisms. As a result, it has become increasingly important to develop computational methods for distinguishing functionally relevant mutations from other variations. We previously developed an algorithm, and now present the web application, CanPredict (http://www.canpredict.org/ or http://www.cgl.ucsf.edu/Research/genentech/canpredict/), to allow users to determine if particular changes are likely to be cancer-associated. The impact of each change is measured using two known methods: Sorting Intolerant From Tolerant (SIFT) and the Pfam-based LogR.E-value metric. A third method, the Gene Ontology Similarity Score (GOSS), provides an indication of how closely the gene in which the variant resides resembles other known cancer-causing genes. Scores from these three algorithms are analyzed by a random forest classifier which then predicts whether a change is likely to be cancer-associated. CanPredict fills an important need in cancer biology and will enable a large audience of biologists to determine which mutations are the most relevant for further study.
Related Links	http://dx.doi.org/10.1093/nar/gkm405
Starting Page	595
File Format	PDF
ISSN	03051048
e-ISSN	13624962
Journal	Nucleic Acids Research
Issue Number	Web Server issue
Volume Number	35
Language	English
Publisher	Oxford University Press
Publisher Date	2007-05-01
Access Restriction	Open
Rights Holder	Oxford University Press
Subject Keyword	Genetics Research in Higher Education
Content Type	Text
Resource Type	Article
Subject	Genetics

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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