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Mining high-throughput experimental data to link gene and function

Paper ID Volume ID Publish Year Pages File Format Full-Text
37224 45325 2011 9 PDF Available
Title
Mining high-throughput experimental data to link gene and function
Abstract

Nearly 2200 genomes that encode around 6 million proteins have now been sequenced. Around 40% of these proteins are of unknown function, even when function is loosely and minimally defined as ‘belonging to a superfamily’. In addition to in silico methods, the swelling stream of high-throughput experimental data can give valuable clues for linking these unknowns with precise biological roles. The goal is to develop integrative data-mining platforms that allow the scientific community at large to access and utilize this rich source of experimental knowledge. To this end, we review recent advances in generating whole-genome experimental datasets, where this data can be accessed, and how it can be used to drive prediction of gene function.

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Publisher
Database: Elsevier - ScienceDirect
Journal: - Volume 29, Issue 4, April 2011, Pages 174–182
Authors
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Subjects
Physical Sciences and Engineering Chemical Engineering Bioengineering
Get Full-Text Now
Don't Miss Today's Special Offer
Price was $35.95
You save - $31
Price after discount Only $4.95
100% Money Back Guarantee
Full-text PDF Download
Online Support
Any Questions? feel free to contact us