PRIN: a predicted rice interactome network

<p>Abstract</p> <p>Background</p> <p>Protein-protein interactions play a fundamental role in elucidating the molecular mechanisms of biomolecular function, signal transductions and metabolic pathways of living organisms. Although high-throughput technologies such as yea...

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Main Authors: Meng Yijun, Jiao Yinming, Zhu Pengcheng, Gu Haibin, Chen Ming
Format: Article
Language:English
Published: BMC 2011-05-01
Series:BMC Bioinformatics
Online Access:http://www.biomedcentral.com/1471-2105/12/161
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spelling doaj-94e70094c0f0460c98a1fd2c0d5110262020-11-25T02:27:12ZengBMCBMC Bioinformatics1471-21052011-05-0112116110.1186/1471-2105-12-161PRIN: a predicted rice interactome networkMeng YijunJiao YinmingZhu PengchengGu HaibinChen Ming<p>Abstract</p> <p>Background</p> <p>Protein-protein interactions play a fundamental role in elucidating the molecular mechanisms of biomolecular function, signal transductions and metabolic pathways of living organisms. Although high-throughput technologies such as yeast two-hybrid system and affinity purification followed by mass spectrometry are widely used in model organisms, the progress of protein-protein interactions detection in plants is rather slow. With this motivation, our work presents a computational approach to predict protein-protein interactions in <it>Oryza sativa</it>.</p> <p>Results</p> <p>To better understand the interactions of proteins in <it>Oryza sativa</it>, we have developed PRIN, a Predicted Rice Interactome Network. Protein-protein interaction data of PRIN are based on the interologs of six model organisms where large-scale protein-protein interaction experiments have been applied: yeast (<it>Saccharomyces cerevisiae</it>), worm (<it>Caenorhabditis elegans</it>), fruit fly (<it>Drosophila melanogaster</it>), human (<it>Homo sapiens</it>), <it>Escherichia coli </it>K12 and <it>Arabidopsis thaliana</it>. With certain quality controls, altogether we obtained 76,585 non-redundant rice protein interaction pairs among 5,049 rice proteins. Further analysis showed that the topology properties of predicted rice protein interaction network are more similar to yeast than to the other 5 organisms. This may not be surprising as the interologs based on yeast contribute nearly 74% of total interactions. In addition, GO annotation, subcellular localization information and gene expression data are also mapped to our network for validation. Finally, a user-friendly web interface was developed to offer convenient database search and network visualization.</p> <p>Conclusions</p> <p>PRIN is the first well annotated protein interaction database for the important model plant <it>Oryza sativa</it>. It has greatly extended the current available protein-protein interaction data of rice with a computational approach, which will certainly provide further insights into rice functional genomics and systems biology.</p> <p>PRIN is available online at <url>http://bis.zju.edu.cn/prin/</url>.</p> http://www.biomedcentral.com/1471-2105/12/161
collection DOAJ
language English
format Article
sources DOAJ
author Meng Yijun
Jiao Yinming
Zhu Pengcheng
Gu Haibin
Chen Ming
spellingShingle Meng Yijun
Jiao Yinming
Zhu Pengcheng
Gu Haibin
Chen Ming
PRIN: a predicted rice interactome network
BMC Bioinformatics
author_facet Meng Yijun
Jiao Yinming
Zhu Pengcheng
Gu Haibin
Chen Ming
author_sort Meng Yijun
title PRIN: a predicted rice interactome network
title_short PRIN: a predicted rice interactome network
title_full PRIN: a predicted rice interactome network
title_fullStr PRIN: a predicted rice interactome network
title_full_unstemmed PRIN: a predicted rice interactome network
title_sort prin: a predicted rice interactome network
publisher BMC
series BMC Bioinformatics
issn 1471-2105
publishDate 2011-05-01
description <p>Abstract</p> <p>Background</p> <p>Protein-protein interactions play a fundamental role in elucidating the molecular mechanisms of biomolecular function, signal transductions and metabolic pathways of living organisms. Although high-throughput technologies such as yeast two-hybrid system and affinity purification followed by mass spectrometry are widely used in model organisms, the progress of protein-protein interactions detection in plants is rather slow. With this motivation, our work presents a computational approach to predict protein-protein interactions in <it>Oryza sativa</it>.</p> <p>Results</p> <p>To better understand the interactions of proteins in <it>Oryza sativa</it>, we have developed PRIN, a Predicted Rice Interactome Network. Protein-protein interaction data of PRIN are based on the interologs of six model organisms where large-scale protein-protein interaction experiments have been applied: yeast (<it>Saccharomyces cerevisiae</it>), worm (<it>Caenorhabditis elegans</it>), fruit fly (<it>Drosophila melanogaster</it>), human (<it>Homo sapiens</it>), <it>Escherichia coli </it>K12 and <it>Arabidopsis thaliana</it>. With certain quality controls, altogether we obtained 76,585 non-redundant rice protein interaction pairs among 5,049 rice proteins. Further analysis showed that the topology properties of predicted rice protein interaction network are more similar to yeast than to the other 5 organisms. This may not be surprising as the interologs based on yeast contribute nearly 74% of total interactions. In addition, GO annotation, subcellular localization information and gene expression data are also mapped to our network for validation. Finally, a user-friendly web interface was developed to offer convenient database search and network visualization.</p> <p>Conclusions</p> <p>PRIN is the first well annotated protein interaction database for the important model plant <it>Oryza sativa</it>. It has greatly extended the current available protein-protein interaction data of rice with a computational approach, which will certainly provide further insights into rice functional genomics and systems biology.</p> <p>PRIN is available online at <url>http://bis.zju.edu.cn/prin/</url>.</p>
url http://www.biomedcentral.com/1471-2105/12/161
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