A novel computational framework for simultaneous integration of multiple types of genomic data to identify microRNA-gene regulatory modules

A novel computational framework for simultaneous integration of multiple types of genomic data to identify microRNA-gene regulatory modules

Motivation: It is well known that microRNAs (miRNAs) and genes work cooperatively to form the key part of gene regulatory networks. However, the specific functional roles of most miRNAs and their combinatorial effects in cellular processes are still unclear. The availability of multiple types of fun...

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Main Authors: Zhang, Shihua, Li, Qingjiao, Liu, Juan, Zhou, Xianghong Jasmine
Format: Online
Language:English
Published: Oxford University Press 2011
Online Access:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3117336/
id pubmed-3117336
recordtype oai_dc
spelling pubmed-31173362011-06-17 A novel computational framework for simultaneous integration of multiple types of genomic data to identify microRNA-gene regulatory modules Zhang, Shihua Li, Qingjiao Liu, Juan Zhou, Xianghong Jasmine Ismb/Eccb 2011 Proceedings Papers Committee July 17 to July 19, 2011, Vienna, Austria Motivation: It is well known that microRNAs (miRNAs) and genes work cooperatively to form the key part of gene regulatory networks. However, the specific functional roles of most miRNAs and their combinatorial effects in cellular processes are still unclear. The availability of multiple types of functional genomic data provides unprecedented opportunities to study the miRNA–gene regulation. A major challenge is how to integrate the diverse genomic data to identify the regulatory modules of miRNAs and genes. Oxford University Press 2011-07-01 2011-06-14 /pmc/articles/PMC3117336/ /pubmed/21685098 http://dx.doi.org/10.1093/bioinformatics/btr206 Text en © The Author(s) 2011. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/2.5 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.5), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
repository_type Open Access Journal
institution_category Foreign Institution
institution US National Center for Biotechnology Information
building NCBI PubMed
collection Online Access
language English
format Online
author Zhang, Shihua
Li, Qingjiao
Liu, Juan
Zhou, Xianghong Jasmine
spellingShingle Zhang, Shihua
Li, Qingjiao
Liu, Juan
Zhou, Xianghong Jasmine
A novel computational framework for simultaneous integration of multiple types of genomic data to identify microRNA-gene regulatory modules
author_facet Zhang, Shihua
Li, Qingjiao
Liu, Juan
Zhou, Xianghong Jasmine
author_sort Zhang, Shihua
title A novel computational framework for simultaneous integration of multiple types of genomic data to identify microRNA-gene regulatory modules
title_short A novel computational framework for simultaneous integration of multiple types of genomic data to identify microRNA-gene regulatory modules
title_full A novel computational framework for simultaneous integration of multiple types of genomic data to identify microRNA-gene regulatory modules
title_fullStr A novel computational framework for simultaneous integration of multiple types of genomic data to identify microRNA-gene regulatory modules
title_full_unstemmed A novel computational framework for simultaneous integration of multiple types of genomic data to identify microRNA-gene regulatory modules
title_sort novel computational framework for simultaneous integration of multiple types of genomic data to identify microrna-gene regulatory modules
description Motivation: It is well known that microRNAs (miRNAs) and genes work cooperatively to form the key part of gene regulatory networks. However, the specific functional roles of most miRNAs and their combinatorial effects in cellular processes are still unclear. The availability of multiple types of functional genomic data provides unprecedented opportunities to study the miRNA–gene regulation. A major challenge is how to integrate the diverse genomic data to identify the regulatory modules of miRNAs and genes.
publisher Oxford University Press
publishDate 2011
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3117336/
_version_ 1611460390162530304

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