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Network modeling of single-cell omics data: challenges, opportunities, and progresses
Single-cell multi-omics technologies are rapidly evolving, prompting both methodological advances and biological discoveries at an unprecedented speed. Gene regulatory network modeling has been used as a powerful approach to elucidate the complex molecular interactions underlying biological processe...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Portland Press Ltd.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7141415/ https://www.ncbi.nlm.nih.gov/pubmed/32270049 http://dx.doi.org/10.1042/ETLS20180176 |
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author | Blencowe, Montgomery Arneson, Douglas Ding, Jessica Chen, Yen-Wei Saleem, Zara Yang, Xia |
author_facet | Blencowe, Montgomery Arneson, Douglas Ding, Jessica Chen, Yen-Wei Saleem, Zara Yang, Xia |
author_sort | Blencowe, Montgomery |
collection | PubMed |
description | Single-cell multi-omics technologies are rapidly evolving, prompting both methodological advances and biological discoveries at an unprecedented speed. Gene regulatory network modeling has been used as a powerful approach to elucidate the complex molecular interactions underlying biological processes and systems, yet its application in single-cell omics data modeling has been met with unique challenges and opportunities. In this review, we discuss these challenges and opportunities, and offer an overview of the recent development of network modeling approaches designed to capture dynamic networks, within-cell networks, and cell–cell interaction or communication networks. Finally, we outline the remaining gaps in single-cell gene network modeling and the outlooks of the field moving forward. |
format | Online Article Text |
id | pubmed-7141415 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Portland Press Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-71414152020-04-08 Network modeling of single-cell omics data: challenges, opportunities, and progresses Blencowe, Montgomery Arneson, Douglas Ding, Jessica Chen, Yen-Wei Saleem, Zara Yang, Xia Emerg Top Life Sci Review Articles Single-cell multi-omics technologies are rapidly evolving, prompting both methodological advances and biological discoveries at an unprecedented speed. Gene regulatory network modeling has been used as a powerful approach to elucidate the complex molecular interactions underlying biological processes and systems, yet its application in single-cell omics data modeling has been met with unique challenges and opportunities. In this review, we discuss these challenges and opportunities, and offer an overview of the recent development of network modeling approaches designed to capture dynamic networks, within-cell networks, and cell–cell interaction or communication networks. Finally, we outline the remaining gaps in single-cell gene network modeling and the outlooks of the field moving forward. Portland Press Ltd. 2019-08-16 2019-07-08 /pmc/articles/PMC7141415/ /pubmed/32270049 http://dx.doi.org/10.1042/ETLS20180176 Text en © 2019 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article published by Portland Press Limited on behalf of the Biochemical Society and the Royal Society of Biology and distributed under the Creative Commons Attribution License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) . |
spellingShingle | Review Articles Blencowe, Montgomery Arneson, Douglas Ding, Jessica Chen, Yen-Wei Saleem, Zara Yang, Xia Network modeling of single-cell omics data: challenges, opportunities, and progresses |
title | Network modeling of single-cell omics data: challenges, opportunities, and progresses |
title_full | Network modeling of single-cell omics data: challenges, opportunities, and progresses |
title_fullStr | Network modeling of single-cell omics data: challenges, opportunities, and progresses |
title_full_unstemmed | Network modeling of single-cell omics data: challenges, opportunities, and progresses |
title_short | Network modeling of single-cell omics data: challenges, opportunities, and progresses |
title_sort | network modeling of single-cell omics data: challenges, opportunities, and progresses |
topic | Review Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7141415/ https://www.ncbi.nlm.nih.gov/pubmed/32270049 http://dx.doi.org/10.1042/ETLS20180176 |
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