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The pain interactome: Connecting pain-specific protein interactions
Understanding the molecular mechanisms associated with disease is a central goal of modern medical research. As such, many thousands of experiments have been published that detail individual molecular events that contribute to a disease. Here we use a semi-automated text mining approach to accuratel...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4247380/ https://www.ncbi.nlm.nih.gov/pubmed/24978826 http://dx.doi.org/10.1016/j.pain.2014.06.020 |
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author | Jamieson, Daniel G. Moss, Andrew Kennedy, Michael Jones, Sherrie Nenadic, Goran Robertson, David L. Sidders, Ben |
author_facet | Jamieson, Daniel G. Moss, Andrew Kennedy, Michael Jones, Sherrie Nenadic, Goran Robertson, David L. Sidders, Ben |
author_sort | Jamieson, Daniel G. |
collection | PubMed |
description | Understanding the molecular mechanisms associated with disease is a central goal of modern medical research. As such, many thousands of experiments have been published that detail individual molecular events that contribute to a disease. Here we use a semi-automated text mining approach to accurately and exhaustively curate the primary literature for chronic pain states. In so doing, we create a comprehensive network of 1,002 contextualized protein–protein interactions (PPIs) specifically associated with pain. The PPIs form a highly interconnected and coherent structure, and the resulting network provides an alternative to those derived from connecting genes associated with pain using interactions that have not been shown to occur in a painful state. We exploit the contextual data associated with our interactions to analyse subnetworks specific to inflammatory and neuropathic pain, and to various anatomical regions. Here, we identify potential targets for further study and several drug-repurposing opportunities. Finally, the network provides a framework for the interpretation of new data within the field of pain. |
format | Online Article Text |
id | pubmed-4247380 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Lippincott Williams & Wilkins |
record_format | MEDLINE/PubMed |
spelling | pubmed-42473802014-12-03 The pain interactome: Connecting pain-specific protein interactions Jamieson, Daniel G. Moss, Andrew Kennedy, Michael Jones, Sherrie Nenadic, Goran Robertson, David L. Sidders, Ben Pain Research Papers Understanding the molecular mechanisms associated with disease is a central goal of modern medical research. As such, many thousands of experiments have been published that detail individual molecular events that contribute to a disease. Here we use a semi-automated text mining approach to accurately and exhaustively curate the primary literature for chronic pain states. In so doing, we create a comprehensive network of 1,002 contextualized protein–protein interactions (PPIs) specifically associated with pain. The PPIs form a highly interconnected and coherent structure, and the resulting network provides an alternative to those derived from connecting genes associated with pain using interactions that have not been shown to occur in a painful state. We exploit the contextual data associated with our interactions to analyse subnetworks specific to inflammatory and neuropathic pain, and to various anatomical regions. Here, we identify potential targets for further study and several drug-repurposing opportunities. Finally, the network provides a framework for the interpretation of new data within the field of pain. Lippincott Williams & Wilkins 2014-11 /pmc/articles/PMC4247380/ /pubmed/24978826 http://dx.doi.org/10.1016/j.pain.2014.06.020 Text en © 2014 The Authors https://creativecommons.org/licenses/by-nc-nd/3.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/). |
spellingShingle | Research Papers Jamieson, Daniel G. Moss, Andrew Kennedy, Michael Jones, Sherrie Nenadic, Goran Robertson, David L. Sidders, Ben The pain interactome: Connecting pain-specific protein interactions |
title | The pain interactome: Connecting pain-specific protein interactions |
title_full | The pain interactome: Connecting pain-specific protein interactions |
title_fullStr | The pain interactome: Connecting pain-specific protein interactions |
title_full_unstemmed | The pain interactome: Connecting pain-specific protein interactions |
title_short | The pain interactome: Connecting pain-specific protein interactions |
title_sort | pain interactome: connecting pain-specific protein interactions |
topic | Research Papers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4247380/ https://www.ncbi.nlm.nih.gov/pubmed/24978826 http://dx.doi.org/10.1016/j.pain.2014.06.020 |
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