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Natural language processing: put your model where your mouth is
Molecular mechanisms are often described using “word models”—phrases intended to capture the interactions in a biological process. In their recent work, Sorger and colleagues (Gyori et al, 2017) provide a framework for converting word models into computational structures that can be simulated and co...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2017
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5740497/ https://www.ncbi.nlm.nih.gov/pubmed/29254950 http://dx.doi.org/10.15252/msb.20178077 |
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author | Haggerty, Rachel A Purvis, Jeremy E |
author_facet | Haggerty, Rachel A Purvis, Jeremy E |
author_sort | Haggerty, Rachel A |
collection | PubMed |
description | Molecular mechanisms are often described using “word models”—phrases intended to capture the interactions in a biological process. In their recent work, Sorger and colleagues (Gyori et al, 2017) provide a framework for converting word models into computational structures that can be simulated and compared to experimental data. By codifying word‐based descriptions of molecular phenomena, scientific communities can better evaluate, compare, and share mechanistic insights. |
format | Online Article Text |
id | pubmed-5740497 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-57404972018-01-02 Natural language processing: put your model where your mouth is Haggerty, Rachel A Purvis, Jeremy E Mol Syst Biol News & Views Molecular mechanisms are often described using “word models”—phrases intended to capture the interactions in a biological process. In their recent work, Sorger and colleagues (Gyori et al, 2017) provide a framework for converting word models into computational structures that can be simulated and compared to experimental data. By codifying word‐based descriptions of molecular phenomena, scientific communities can better evaluate, compare, and share mechanistic insights. John Wiley and Sons Inc. 2017-12-18 /pmc/articles/PMC5740497/ /pubmed/29254950 http://dx.doi.org/10.15252/msb.20178077 Text en © 2017 The Authors. Published under the terms of the CC BY 4.0 license This is an open access article under the terms of the Creative Commons Attribution 4.0 (http://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | News & Views Haggerty, Rachel A Purvis, Jeremy E Natural language processing: put your model where your mouth is |
title | Natural language processing: put your model where your mouth is |
title_full | Natural language processing: put your model where your mouth is |
title_fullStr | Natural language processing: put your model where your mouth is |
title_full_unstemmed | Natural language processing: put your model where your mouth is |
title_short | Natural language processing: put your model where your mouth is |
title_sort | natural language processing: put your model where your mouth is |
topic | News & Views |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5740497/ https://www.ncbi.nlm.nih.gov/pubmed/29254950 http://dx.doi.org/10.15252/msb.20178077 |
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