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Big data in basic and translational cancer research
Historically, the primary focus of cancer research has been molecular and clinical studies of a few essential pathways and genes. Recent years have seen the rapid accumulation of large-scale cancer omics data catalysed by breakthroughs in high-throughput technologies. This fast data growth has given...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9443637/ https://www.ncbi.nlm.nih.gov/pubmed/36064595 http://dx.doi.org/10.1038/s41568-022-00502-0 |
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author | Jiang, Peng Sinha, Sanju Aldape, Kenneth Hannenhalli, Sridhar Sahinalp, Cenk Ruppin, Eytan |
author_facet | Jiang, Peng Sinha, Sanju Aldape, Kenneth Hannenhalli, Sridhar Sahinalp, Cenk Ruppin, Eytan |
author_sort | Jiang, Peng |
collection | PubMed |
description | Historically, the primary focus of cancer research has been molecular and clinical studies of a few essential pathways and genes. Recent years have seen the rapid accumulation of large-scale cancer omics data catalysed by breakthroughs in high-throughput technologies. This fast data growth has given rise to an evolving concept of ‘big data’ in cancer, whose analysis demands large computational resources and can potentially bring novel insights into essential questions. Indeed, the combination of big data, bioinformatics and artificial intelligence has led to notable advances in our basic understanding of cancer biology and to translational advancements. Further advances will require a concerted effort among data scientists, clinicians, biologists and policymakers. Here, we review the current state of the art and future challenges for harnessing big data to advance cancer research and treatment. |
format | Online Article Text |
id | pubmed-9443637 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-94436372022-09-06 Big data in basic and translational cancer research Jiang, Peng Sinha, Sanju Aldape, Kenneth Hannenhalli, Sridhar Sahinalp, Cenk Ruppin, Eytan Nat Rev Cancer Review Article Historically, the primary focus of cancer research has been molecular and clinical studies of a few essential pathways and genes. Recent years have seen the rapid accumulation of large-scale cancer omics data catalysed by breakthroughs in high-throughput technologies. This fast data growth has given rise to an evolving concept of ‘big data’ in cancer, whose analysis demands large computational resources and can potentially bring novel insights into essential questions. Indeed, the combination of big data, bioinformatics and artificial intelligence has led to notable advances in our basic understanding of cancer biology and to translational advancements. Further advances will require a concerted effort among data scientists, clinicians, biologists and policymakers. Here, we review the current state of the art and future challenges for harnessing big data to advance cancer research and treatment. Nature Publishing Group UK 2022-09-05 2022 /pmc/articles/PMC9443637/ /pubmed/36064595 http://dx.doi.org/10.1038/s41568-022-00502-0 Text en © This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2022, Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Review Article Jiang, Peng Sinha, Sanju Aldape, Kenneth Hannenhalli, Sridhar Sahinalp, Cenk Ruppin, Eytan Big data in basic and translational cancer research |
title | Big data in basic and translational cancer research |
title_full | Big data in basic and translational cancer research |
title_fullStr | Big data in basic and translational cancer research |
title_full_unstemmed | Big data in basic and translational cancer research |
title_short | Big data in basic and translational cancer research |
title_sort | big data in basic and translational cancer research |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9443637/ https://www.ncbi.nlm.nih.gov/pubmed/36064595 http://dx.doi.org/10.1038/s41568-022-00502-0 |
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