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The MultiOmics Explainer: explaining omics results in the context of a pathway/genome database
BACKGROUND: High-throughput experiments can bring to light associations between genes, proteins and/or metabolites, many of which will be explainable by existing knowledge. Our aim is to speed elucidation of such explanations and, in some cases, find explanations that scientists might otherwise over...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6637615/ https://www.ncbi.nlm.nih.gov/pubmed/31319812 http://dx.doi.org/10.1186/s12859-019-2971-6 |
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author | Paley, Suzanne Karp, Peter D. |
author_facet | Paley, Suzanne Karp, Peter D. |
author_sort | Paley, Suzanne |
collection | PubMed |
description | BACKGROUND: High-throughput experiments can bring to light associations between genes, proteins and/or metabolites, many of which will be explainable by existing knowledge. Our aim is to speed elucidation of such explanations and, in some cases, find explanations that scientists might otherwise overlook. RESULTS: We describe the MultiOmics Explainer, a new tool within the Pathway Tools software suite that leverages what is known about an organism’s metabolic and regulatory network to suggest explanations for the results of omics experiments. Querying a database such as EcoCyc, the MultiOmics Explainer searches the organism’s network of metabolic reactions, transporters, cofactors, enzyme substrate-level activation and inhibition relationships, and transcriptional and translational regulation relationships to identify paths of influence among input genes, proteins and metabolites. Results are presented in a combined metabolic and regulatory diagram. We present several examples of explanations generated for associations found in the Escherichia coli literature. CONCLUSIONS: The MultiOmics Explainer is a valuable tool that helps researchers understand and interpret the results of their omics experiments in the context of what is known about an organism’s metabolic and regulatory network. It showcases the rich set of computational inferences that can be drawn from a database such as EcoCyc that encodes a diverse range of biological interactions. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-019-2971-6) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6637615 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-66376152019-07-25 The MultiOmics Explainer: explaining omics results in the context of a pathway/genome database Paley, Suzanne Karp, Peter D. BMC Bioinformatics Software BACKGROUND: High-throughput experiments can bring to light associations between genes, proteins and/or metabolites, many of which will be explainable by existing knowledge. Our aim is to speed elucidation of such explanations and, in some cases, find explanations that scientists might otherwise overlook. RESULTS: We describe the MultiOmics Explainer, a new tool within the Pathway Tools software suite that leverages what is known about an organism’s metabolic and regulatory network to suggest explanations for the results of omics experiments. Querying a database such as EcoCyc, the MultiOmics Explainer searches the organism’s network of metabolic reactions, transporters, cofactors, enzyme substrate-level activation and inhibition relationships, and transcriptional and translational regulation relationships to identify paths of influence among input genes, proteins and metabolites. Results are presented in a combined metabolic and regulatory diagram. We present several examples of explanations generated for associations found in the Escherichia coli literature. CONCLUSIONS: The MultiOmics Explainer is a valuable tool that helps researchers understand and interpret the results of their omics experiments in the context of what is known about an organism’s metabolic and regulatory network. It showcases the rich set of computational inferences that can be drawn from a database such as EcoCyc that encodes a diverse range of biological interactions. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-019-2971-6) contains supplementary material, which is available to authorized users. BioMed Central 2019-07-18 /pmc/articles/PMC6637615/ /pubmed/31319812 http://dx.doi.org/10.1186/s12859-019-2971-6 Text en © The Author(s) 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License(http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Software Paley, Suzanne Karp, Peter D. The MultiOmics Explainer: explaining omics results in the context of a pathway/genome database |
title | The MultiOmics Explainer: explaining omics results in the context of a pathway/genome database |
title_full | The MultiOmics Explainer: explaining omics results in the context of a pathway/genome database |
title_fullStr | The MultiOmics Explainer: explaining omics results in the context of a pathway/genome database |
title_full_unstemmed | The MultiOmics Explainer: explaining omics results in the context of a pathway/genome database |
title_short | The MultiOmics Explainer: explaining omics results in the context of a pathway/genome database |
title_sort | multiomics explainer: explaining omics results in the context of a pathway/genome database |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6637615/ https://www.ncbi.nlm.nih.gov/pubmed/31319812 http://dx.doi.org/10.1186/s12859-019-2971-6 |
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