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Relative specificity as an important consideration in the big data era
Technological breakthroughs such as high-throughput methods, genomics, single-cell studies, and machine learning have fundamentally transformed research and ushered in the big data era of biology. Nevertheless, current data collections, analyses, and modeling frequently overlook relative specificity...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9582229/ https://www.ncbi.nlm.nih.gov/pubmed/36276983 http://dx.doi.org/10.3389/fgene.2022.1030415 |
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author | Zhang, Xiaoxiao Zeng, Yan |
author_facet | Zhang, Xiaoxiao Zeng, Yan |
author_sort | Zhang, Xiaoxiao |
collection | PubMed |
description | Technological breakthroughs such as high-throughput methods, genomics, single-cell studies, and machine learning have fundamentally transformed research and ushered in the big data era of biology. Nevertheless, current data collections, analyses, and modeling frequently overlook relative specificity, a crucial property of molecular interactions in biochemical systems. Relative specificity describes how, for example, an enzyme reacts with its many substrates at different rates, and how this discriminatory action alone is sufficient to modulate the substrates and downstream events. As a corollary, it is not only important to comprehensively identify an enzyme’s substrates, but also critical to quantitatively determine how the enzyme interacts with the substrates and to evaluate how it shapes subsequent biological outcomes. Genomics and high-throughput techniques have greatly facilitated the studies of relative specificity in the 21st century, and its functional significance has been demonstrated in complex biochemical systems including transcription, translation, protein kinases, RNA-binding proteins, and animal microRNAs (miRNAs), although it remains ignored in most work. Here we analyze recent findings in big data and relative specificity studies and explain how the incorporation of relative specificity concept might enhance our mechanistic understanding of gene functions, biological phenomena, and human diseases. |
format | Online Article Text |
id | pubmed-9582229 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-95822292022-10-21 Relative specificity as an important consideration in the big data era Zhang, Xiaoxiao Zeng, Yan Front Genet Genetics Technological breakthroughs such as high-throughput methods, genomics, single-cell studies, and machine learning have fundamentally transformed research and ushered in the big data era of biology. Nevertheless, current data collections, analyses, and modeling frequently overlook relative specificity, a crucial property of molecular interactions in biochemical systems. Relative specificity describes how, for example, an enzyme reacts with its many substrates at different rates, and how this discriminatory action alone is sufficient to modulate the substrates and downstream events. As a corollary, it is not only important to comprehensively identify an enzyme’s substrates, but also critical to quantitatively determine how the enzyme interacts with the substrates and to evaluate how it shapes subsequent biological outcomes. Genomics and high-throughput techniques have greatly facilitated the studies of relative specificity in the 21st century, and its functional significance has been demonstrated in complex biochemical systems including transcription, translation, protein kinases, RNA-binding proteins, and animal microRNAs (miRNAs), although it remains ignored in most work. Here we analyze recent findings in big data and relative specificity studies and explain how the incorporation of relative specificity concept might enhance our mechanistic understanding of gene functions, biological phenomena, and human diseases. Frontiers Media S.A. 2022-10-06 /pmc/articles/PMC9582229/ /pubmed/36276983 http://dx.doi.org/10.3389/fgene.2022.1030415 Text en Copyright © 2022 Zhang and Zeng. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Zhang, Xiaoxiao Zeng, Yan Relative specificity as an important consideration in the big data era |
title | Relative specificity as an important consideration in the big data era |
title_full | Relative specificity as an important consideration in the big data era |
title_fullStr | Relative specificity as an important consideration in the big data era |
title_full_unstemmed | Relative specificity as an important consideration in the big data era |
title_short | Relative specificity as an important consideration in the big data era |
title_sort | relative specificity as an important consideration in the big data era |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9582229/ https://www.ncbi.nlm.nih.gov/pubmed/36276983 http://dx.doi.org/10.3389/fgene.2022.1030415 |
work_keys_str_mv | AT zhangxiaoxiao relativespecificityasanimportantconsiderationinthebigdataera AT zengyan relativespecificityasanimportantconsiderationinthebigdataera |