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Biological Process Linkage Networks

BACKGROUND: The traditional approach to studying complex biological networks is based on the identification of interactions between internal components of signaling or metabolic pathways. By comparison, little is known about interactions between higher order biological systems, such as biological pa...

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Detalles Bibliográficos
Autores principales: Dotan-Cohen, Dikla, Letovsky, Stan, Melkman, Avraham A., Kasif, Simon
Formato: Texto
Lenguaje:English
Publicado: Public Library of Science 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2669181/
https://www.ncbi.nlm.nih.gov/pubmed/19390589
http://dx.doi.org/10.1371/journal.pone.0005313
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author Dotan-Cohen, Dikla
Letovsky, Stan
Melkman, Avraham A.
Kasif, Simon
author_facet Dotan-Cohen, Dikla
Letovsky, Stan
Melkman, Avraham A.
Kasif, Simon
author_sort Dotan-Cohen, Dikla
collection PubMed
description BACKGROUND: The traditional approach to studying complex biological networks is based on the identification of interactions between internal components of signaling or metabolic pathways. By comparison, little is known about interactions between higher order biological systems, such as biological pathways and processes. We propose a methodology for gleaning patterns of interactions between biological processes by analyzing protein-protein interactions, transcriptional co-expression and genetic interactions. At the heart of the methodology are the concept of Linked Processes and the resultant network of biological processes, the Process Linkage Network (PLN). RESULTS: We construct, catalogue, and analyze different types of PLNs derived from different data sources and different species. When applied to the Gene Ontology, many of the resulting links connect processes that are distant from each other in the hierarchy, even though the connection makes eminent sense biologically. Some others, however, carry an element of surprise and may reflect mechanisms that are unique to the organism under investigation. In this aspect our method complements the link structure between processes inherent in the Gene Ontology, which by its very nature is species-independent. As a practical application of the linkage of processes we demonstrate that it can be effectively used in protein function prediction, having the power to increase both the coverage and the accuracy of predictions, when carefully integrated into prediction methods. CONCLUSIONS: Our approach constitutes a promising new direction towards understanding the higher levels of organization of the cell as a system which should help current efforts to re-engineer ontologies and improve our ability to predict which proteins are involved in specific biological processes.
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spelling pubmed-26691812009-04-23 Biological Process Linkage Networks Dotan-Cohen, Dikla Letovsky, Stan Melkman, Avraham A. Kasif, Simon PLoS One Research Article BACKGROUND: The traditional approach to studying complex biological networks is based on the identification of interactions between internal components of signaling or metabolic pathways. By comparison, little is known about interactions between higher order biological systems, such as biological pathways and processes. We propose a methodology for gleaning patterns of interactions between biological processes by analyzing protein-protein interactions, transcriptional co-expression and genetic interactions. At the heart of the methodology are the concept of Linked Processes and the resultant network of biological processes, the Process Linkage Network (PLN). RESULTS: We construct, catalogue, and analyze different types of PLNs derived from different data sources and different species. When applied to the Gene Ontology, many of the resulting links connect processes that are distant from each other in the hierarchy, even though the connection makes eminent sense biologically. Some others, however, carry an element of surprise and may reflect mechanisms that are unique to the organism under investigation. In this aspect our method complements the link structure between processes inherent in the Gene Ontology, which by its very nature is species-independent. As a practical application of the linkage of processes we demonstrate that it can be effectively used in protein function prediction, having the power to increase both the coverage and the accuracy of predictions, when carefully integrated into prediction methods. CONCLUSIONS: Our approach constitutes a promising new direction towards understanding the higher levels of organization of the cell as a system which should help current efforts to re-engineer ontologies and improve our ability to predict which proteins are involved in specific biological processes. Public Library of Science 2009-04-23 /pmc/articles/PMC2669181/ /pubmed/19390589 http://dx.doi.org/10.1371/journal.pone.0005313 Text en Dotan-Cohen et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Dotan-Cohen, Dikla
Letovsky, Stan
Melkman, Avraham A.
Kasif, Simon
Biological Process Linkage Networks
title Biological Process Linkage Networks
title_full Biological Process Linkage Networks
title_fullStr Biological Process Linkage Networks
title_full_unstemmed Biological Process Linkage Networks
title_short Biological Process Linkage Networks
title_sort biological process linkage networks
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2669181/
https://www.ncbi.nlm.nih.gov/pubmed/19390589
http://dx.doi.org/10.1371/journal.pone.0005313
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