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Counting motifs in the human interactome

Small over-represented motifs in biological networks often form essential functional units of biological processes. A natural question is to gauge whether a motif occurs abundantly or rarely in a biological network. Here we develop an accurate method to estimate the occurrences of a motif in the ent...

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Detalles Bibliográficos
Autores principales: Tran, Ngoc Hieu, Choi, Kwok Pui, Zhang, Louxin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Pub. Group 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3741638/
https://www.ncbi.nlm.nih.gov/pubmed/23917172
http://dx.doi.org/10.1038/ncomms3241
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author Tran, Ngoc Hieu
Choi, Kwok Pui
Zhang, Louxin
author_facet Tran, Ngoc Hieu
Choi, Kwok Pui
Zhang, Louxin
author_sort Tran, Ngoc Hieu
collection PubMed
description Small over-represented motifs in biological networks often form essential functional units of biological processes. A natural question is to gauge whether a motif occurs abundantly or rarely in a biological network. Here we develop an accurate method to estimate the occurrences of a motif in the entire network from noisy and incomplete data, and apply it to eukaryotic interactomes and cell-specific transcription factor regulatory networks. The number of triangles in the human interactome is about 194 times that in the Saccharomyces cerevisiae interactome. A strong positive linear correlation exists between the numbers of occurrences of triad and quadriad motifs in human cell-specific transcription factor regulatory networks. Our findings show that the proposed method is general and powerful for counting motifs and can be applied to any network regardless of its topological structure.
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spelling pubmed-37416382013-08-13 Counting motifs in the human interactome Tran, Ngoc Hieu Choi, Kwok Pui Zhang, Louxin Nat Commun Article Small over-represented motifs in biological networks often form essential functional units of biological processes. A natural question is to gauge whether a motif occurs abundantly or rarely in a biological network. Here we develop an accurate method to estimate the occurrences of a motif in the entire network from noisy and incomplete data, and apply it to eukaryotic interactomes and cell-specific transcription factor regulatory networks. The number of triangles in the human interactome is about 194 times that in the Saccharomyces cerevisiae interactome. A strong positive linear correlation exists between the numbers of occurrences of triad and quadriad motifs in human cell-specific transcription factor regulatory networks. Our findings show that the proposed method is general and powerful for counting motifs and can be applied to any network regardless of its topological structure. Nature Pub. Group 2013-08-06 /pmc/articles/PMC3741638/ /pubmed/23917172 http://dx.doi.org/10.1038/ncomms3241 Text en Copyright © 2013, Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved. http://creativecommons.org/licenses/by-nc-sa/3.0/ This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/3.0/
spellingShingle Article
Tran, Ngoc Hieu
Choi, Kwok Pui
Zhang, Louxin
Counting motifs in the human interactome
title Counting motifs in the human interactome
title_full Counting motifs in the human interactome
title_fullStr Counting motifs in the human interactome
title_full_unstemmed Counting motifs in the human interactome
title_short Counting motifs in the human interactome
title_sort counting motifs in the human interactome
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3741638/
https://www.ncbi.nlm.nih.gov/pubmed/23917172
http://dx.doi.org/10.1038/ncomms3241
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