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Identifying and Analyzing Topic Clusters in a Nutri-, Food-, and Diet-Proteomic Corpus Using Machine Reading
Nutrition affects the early stages of disease development, but the mechanisms remain poorly understood. High-throughput proteomic methods are being used to generate data and information on the effects of nutrients, foods, and diets on health and disease processes. In this report, a novel machine rea...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9863309/ https://www.ncbi.nlm.nih.gov/pubmed/36678141 http://dx.doi.org/10.3390/nu15020270 |
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author | Monteiro, Jacqueline Pontes Morine, Melissa J. Ued, Fabio V. Kaput, Jim |
author_facet | Monteiro, Jacqueline Pontes Morine, Melissa J. Ued, Fabio V. Kaput, Jim |
author_sort | Monteiro, Jacqueline Pontes |
collection | PubMed |
description | Nutrition affects the early stages of disease development, but the mechanisms remain poorly understood. High-throughput proteomic methods are being used to generate data and information on the effects of nutrients, foods, and diets on health and disease processes. In this report, a novel machine reading pipeline was used to identify all articles and abstracts on proteomics, diet, food, and nutrition in humans. The resulting proteomic corpus was further analyzed to produce seven clusters of “thematic” content defined as documents that have similar word content. Examples of publications from several of these clusters were then described in a similar way to a typical descriptive review. |
format | Online Article Text |
id | pubmed-9863309 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-98633092023-01-22 Identifying and Analyzing Topic Clusters in a Nutri-, Food-, and Diet-Proteomic Corpus Using Machine Reading Monteiro, Jacqueline Pontes Morine, Melissa J. Ued, Fabio V. Kaput, Jim Nutrients Review Nutrition affects the early stages of disease development, but the mechanisms remain poorly understood. High-throughput proteomic methods are being used to generate data and information on the effects of nutrients, foods, and diets on health and disease processes. In this report, a novel machine reading pipeline was used to identify all articles and abstracts on proteomics, diet, food, and nutrition in humans. The resulting proteomic corpus was further analyzed to produce seven clusters of “thematic” content defined as documents that have similar word content. Examples of publications from several of these clusters were then described in a similar way to a typical descriptive review. MDPI 2023-01-05 /pmc/articles/PMC9863309/ /pubmed/36678141 http://dx.doi.org/10.3390/nu15020270 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Monteiro, Jacqueline Pontes Morine, Melissa J. Ued, Fabio V. Kaput, Jim Identifying and Analyzing Topic Clusters in a Nutri-, Food-, and Diet-Proteomic Corpus Using Machine Reading |
title | Identifying and Analyzing Topic Clusters in a Nutri-, Food-, and Diet-Proteomic Corpus Using Machine Reading |
title_full | Identifying and Analyzing Topic Clusters in a Nutri-, Food-, and Diet-Proteomic Corpus Using Machine Reading |
title_fullStr | Identifying and Analyzing Topic Clusters in a Nutri-, Food-, and Diet-Proteomic Corpus Using Machine Reading |
title_full_unstemmed | Identifying and Analyzing Topic Clusters in a Nutri-, Food-, and Diet-Proteomic Corpus Using Machine Reading |
title_short | Identifying and Analyzing Topic Clusters in a Nutri-, Food-, and Diet-Proteomic Corpus Using Machine Reading |
title_sort | identifying and analyzing topic clusters in a nutri-, food-, and diet-proteomic corpus using machine reading |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9863309/ https://www.ncbi.nlm.nih.gov/pubmed/36678141 http://dx.doi.org/10.3390/nu15020270 |
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