Open Access
Nucleic Acids Research, volume 50, issue W1, pages W690-W696
Shiny GATOM: omics-based identification of regulated metabolic modules in atom transition networks
Emelianova Mariia
1
,
Gainullina Anastasiia
1, 2
,
Poperechnyi Nikolay
1
,
Loboda Alexander
1
,
Artyomov Maxim
1, 3
,
Sergushichev Alexey
1, 3
3
Department of Pathology and Immunology, Washington University in St. Louis , St. Louis , MO 63110 , USA
|
Publication type: Journal Article
Publication date: 2022-05-27
Journal:
Nucleic Acids Research
Quartile SCImago
Q1
Quartile WOS
Q1
Impact factor: 14.9
ISSN: 03051048, 13624962
PubMed ID:
35639928
Genetics
Abstract
Multiple high-throughput omics techniques provide different angles on systematically quantifying and studying metabolic regulation of cellular processes. However, an unbiased analysis of such data and, in particular, integration of multiple types of data remains a challenge. Previously, for this purpose we developed GAM web-service for integrative metabolic network analysis. Here we describe an updated pipeline GATOM and the corresponding web-service Shiny GATOM, which takes as input transcriptional and/or metabolomic data and finds a metabolic subnetwork most regulated between the two conditions of interest. GATOM features a new metabolic network topology based on atom transition, which significantly improves interpretability of the analysis results. To address computational challenges arising with the new network topology, we introduce a new variant of the maximum weight connected subgraph problem and provide a corresponding exact solver. To make the used networks up-to-date we upgraded the KEGG-based network construction pipeline and developed one based on the Rhea database, which allows analysis of lipidomics data. Finally, we simplified local installation, providing R package mwcsr for solving relevant graph optimization problems and R package gatom, which implements the GATOM pipeline. The web-service is available at https://ctlab.itmo.ru/shiny/gatom and https://artyomovlab.wustl.edu/shiny/gatom.
Citations by journals
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1
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Cell Reports
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Cell Reports
1 publication, 25%
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Annual Review of Immunology
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1 publication, 25%
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Briefings in Bioinformatics
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Computational and Structural Biotechnology Journal
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1 publication, 25%
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1
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Citations by publishers
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1
2
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Elsevier
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Elsevier
2 publications, 50%
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Annual Reviews
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Annual Reviews
1 publication, 25%
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Oxford University Press
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Oxford University Press
1 publication, 25%
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1
2
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- We do not take into account publications that without a DOI.
- Statistics recalculated only for publications connected to researchers, organizations and labs registered on the platform.
- Statistics recalculated weekly.
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Emelianova M. et al. Shiny GATOM: omics-based identification of regulated metabolic modules in atom transition networks // Nucleic Acids Research. 2022. Vol. 50. No. W1. p. W690-W696.
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Emelianova M., Gainullina A., Poperechnyi N., Loboda A., Artyomov M., Sergushichev A. Shiny GATOM: omics-based identification of regulated metabolic modules in atom transition networks // Nucleic Acids Research. 2022. Vol. 50. No. W1. p. W690-W696.
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TY - JOUR
DO - 10.1093/nar/gkac427
UR - https://doi.org/10.1093%2Fnar%2Fgkac427
TI - Shiny GATOM: omics-based identification of regulated metabolic modules in atom transition networks
T2 - Nucleic Acids Research
AU - Emelianova, Mariia
AU - Gainullina, Anastasiia
AU - Poperechnyi, Nikolay
AU - Loboda, Alexander
AU - Artyomov, Maxim
AU - Sergushichev, Alexey
PY - 2022
DA - 2022/05/27 00:00:00
PB - Oxford University Press
SP - W690-W696
IS - W1
VL - 50
PMID - 35639928
SN - 0305-1048
SN - 1362-4962
ER -
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@article{2022_Emelianova,
author = {Mariia Emelianova and Anastasiia Gainullina and Nikolay Poperechnyi and Alexander Loboda and Maxim Artyomov and Alexey Sergushichev},
title = {Shiny GATOM: omics-based identification of regulated metabolic modules in atom transition networks},
journal = {Nucleic Acids Research},
year = {2022},
volume = {50},
publisher = {Oxford University Press},
month = {may},
url = {https://doi.org/10.1093%2Fnar%2Fgkac427},
number = {W1},
pages = {W690--W696},
doi = {10.1093/nar/gkac427}
}
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MLA
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Emelianova, Mariia, et al. “Shiny GATOM: omics-based identification of regulated metabolic modules in atom transition networks.” Nucleic Acids Research, vol. 50, no. W1, May. 2022, pp. W690-W696. https://doi.org/10.1093%2Fnar%2Fgkac427.