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Transcriptome data modeling for targeted plant metabolic engineering

Paper ID Volume ID Publish Year Pages File Format Full-Text
15941 42478 2013 6 PDF Available
Title
Transcriptome data modeling for targeted plant metabolic engineering
Abstract

The massive data generated by omics technologies require the power of bioinformatics, especially network analysis, for data mining and doing data-driven biology. Gene coexpression analysis, a network approach based on comprehensive gene expression data using microarrays, is becoming a standard tool for predicting gene function and elucidating the relationship between metabolic pathways. Differential and comparative gene coexpression analyses suggest a change in coexpression relationships and regulators controlling common and/or specific biological processes. In conjunction with the newly emerging genome editing technology, network analysis integrated with other omics data should pave the way for robust and practical plant metabolic engineering.

Graphical abstractFigure optionsDownload full-size imageDownload high-quality image (235 K)Download as PowerPoint slideHighlights► Network analysis is essential for data mining of omics-based large-scale data sets. ► Gene coexpression analysis is useful for prediction of gene function. ► Comparative network analysis can reveal common and unique plant metabolic pathways. ► Novel genome editing tools facilitate rational metabolic engineering.

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Transcriptome data modeling for targeted plant metabolic engineering
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Publisher
Database: Elsevier - ScienceDirect
Journal: Current Opinion in Biotechnology - Volume 24, Issue 2, April 2013, Pages 285–290
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