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From time-series transcriptomics to gene regulatory networks: A review on inference methods
Inference of gene regulatory networks has been an active area of research for around 20 years, leading to the development of sophisticated inference algorithms based on a variety of assumptions and approaches. With the ever increasing demand for more accurate and powerful models, the inference probl...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Public Library of Science
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10414591/ https://www.ncbi.nlm.nih.gov/pubmed/37561790 http://dx.doi.org/10.1371/journal.pcbi.1011254 |
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author | Marku, Malvina Pancaldi, Vera |
author_facet | Marku, Malvina Pancaldi, Vera |
author_sort | Marku, Malvina |
collection | PubMed |
description | Inference of gene regulatory networks has been an active area of research for around 20 years, leading to the development of sophisticated inference algorithms based on a variety of assumptions and approaches. With the ever increasing demand for more accurate and powerful models, the inference problem remains of broad scientific interest. The abstract representation of biological systems through gene regulatory networks represents a powerful method to study such systems, encoding different amounts and types of information. In this review, we summarize the different types of inference algorithms specifically based on time-series transcriptomics, giving an overview of the main applications of gene regulatory networks in computational biology. This review is intended to give an updated reference of regulatory networks inference tools to biologists and researchers new to the topic and guide them in selecting the appropriate inference method that best fits their questions, aims, and experimental data. |
format | Online Article Text |
id | pubmed-10414591 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-104145912023-08-11 From time-series transcriptomics to gene regulatory networks: A review on inference methods Marku, Malvina Pancaldi, Vera PLoS Comput Biol Review Inference of gene regulatory networks has been an active area of research for around 20 years, leading to the development of sophisticated inference algorithms based on a variety of assumptions and approaches. With the ever increasing demand for more accurate and powerful models, the inference problem remains of broad scientific interest. The abstract representation of biological systems through gene regulatory networks represents a powerful method to study such systems, encoding different amounts and types of information. In this review, we summarize the different types of inference algorithms specifically based on time-series transcriptomics, giving an overview of the main applications of gene regulatory networks in computational biology. This review is intended to give an updated reference of regulatory networks inference tools to biologists and researchers new to the topic and guide them in selecting the appropriate inference method that best fits their questions, aims, and experimental data. Public Library of Science 2023-08-10 /pmc/articles/PMC10414591/ /pubmed/37561790 http://dx.doi.org/10.1371/journal.pcbi.1011254 Text en © 2023 Marku, Pancaldi https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Review Marku, Malvina Pancaldi, Vera From time-series transcriptomics to gene regulatory networks: A review on inference methods |
title | From time-series transcriptomics to gene regulatory networks: A review on inference methods |
title_full | From time-series transcriptomics to gene regulatory networks: A review on inference methods |
title_fullStr | From time-series transcriptomics to gene regulatory networks: A review on inference methods |
title_full_unstemmed | From time-series transcriptomics to gene regulatory networks: A review on inference methods |
title_short | From time-series transcriptomics to gene regulatory networks: A review on inference methods |
title_sort | from time-series transcriptomics to gene regulatory networks: a review on inference methods |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10414591/ https://www.ncbi.nlm.nih.gov/pubmed/37561790 http://dx.doi.org/10.1371/journal.pcbi.1011254 |
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