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NetControl4BioMed: a pipeline for biomedical data acquisition and analysis of network controllability
BACKGROUND: Network controllability focuses on discovering combinations of external interventions that can drive a biological system to a desired configuration. In practice, this approach translates into finding a combined multi-drug therapy in order to induce a desired response from a cell; this ca...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6069765/ https://www.ncbi.nlm.nih.gov/pubmed/30066633 http://dx.doi.org/10.1186/s12859-018-2177-3 |
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author | Kanhaiya, Krishna Rogojin, Vladimir Kazemi, Keivan Czeizler, Eugen Petre, Ion |
author_facet | Kanhaiya, Krishna Rogojin, Vladimir Kazemi, Keivan Czeizler, Eugen Petre, Ion |
author_sort | Kanhaiya, Krishna |
collection | PubMed |
description | BACKGROUND: Network controllability focuses on discovering combinations of external interventions that can drive a biological system to a desired configuration. In practice, this approach translates into finding a combined multi-drug therapy in order to induce a desired response from a cell; this can lead to developments of novel therapeutic approaches for systemic diseases like cancer. RESULT: We develop a novel bioinformatics data analysis pipeline called NetControl4BioMed based on the concept of target structural control of linear networks. Our pipeline generates novel molecular interaction networks by combining pathway data from various public databases starting from the user’s query. The pipeline then identifies a set of nodes that is enough to control a given, user-defined set of disease-specific essential proteins in the network, i.e., it is able to induce a change in their configuration from any initial state to any final state. We provide both the source code of the pipeline as well as an online web-service based on this pipeline http://combio.abo.fi/nc/net_control/remote_call.php. CONCLUSION: The pipeline can be used by researchers for controlling and better understanding of molecular interaction networks through combinatorial multi-drug therapies, for more efficient therapeutic approaches and personalised medicine. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-018-2177-3) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6069765 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-60697652018-08-03 NetControl4BioMed: a pipeline for biomedical data acquisition and analysis of network controllability Kanhaiya, Krishna Rogojin, Vladimir Kazemi, Keivan Czeizler, Eugen Petre, Ion BMC Bioinformatics Software BACKGROUND: Network controllability focuses on discovering combinations of external interventions that can drive a biological system to a desired configuration. In practice, this approach translates into finding a combined multi-drug therapy in order to induce a desired response from a cell; this can lead to developments of novel therapeutic approaches for systemic diseases like cancer. RESULT: We develop a novel bioinformatics data analysis pipeline called NetControl4BioMed based on the concept of target structural control of linear networks. Our pipeline generates novel molecular interaction networks by combining pathway data from various public databases starting from the user’s query. The pipeline then identifies a set of nodes that is enough to control a given, user-defined set of disease-specific essential proteins in the network, i.e., it is able to induce a change in their configuration from any initial state to any final state. We provide both the source code of the pipeline as well as an online web-service based on this pipeline http://combio.abo.fi/nc/net_control/remote_call.php. CONCLUSION: The pipeline can be used by researchers for controlling and better understanding of molecular interaction networks through combinatorial multi-drug therapies, for more efficient therapeutic approaches and personalised medicine. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-018-2177-3) contains supplementary material, which is available to authorized users. BioMed Central 2018-07-09 /pmc/articles/PMC6069765/ /pubmed/30066633 http://dx.doi.org/10.1186/s12859-018-2177-3 Text en © The Author(s) 2018 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 Kanhaiya, Krishna Rogojin, Vladimir Kazemi, Keivan Czeizler, Eugen Petre, Ion NetControl4BioMed: a pipeline for biomedical data acquisition and analysis of network controllability |
title | NetControl4BioMed: a pipeline for biomedical data acquisition and analysis of network controllability |
title_full | NetControl4BioMed: a pipeline for biomedical data acquisition and analysis of network controllability |
title_fullStr | NetControl4BioMed: a pipeline for biomedical data acquisition and analysis of network controllability |
title_full_unstemmed | NetControl4BioMed: a pipeline for biomedical data acquisition and analysis of network controllability |
title_short | NetControl4BioMed: a pipeline for biomedical data acquisition and analysis of network controllability |
title_sort | netcontrol4biomed: a pipeline for biomedical data acquisition and analysis of network controllability |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6069765/ https://www.ncbi.nlm.nih.gov/pubmed/30066633 http://dx.doi.org/10.1186/s12859-018-2177-3 |
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