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Big data in basic and translational cancer research.
Jiang, Peng; Sinha, Sanju; Aldape, Kenneth; Hannenhalli, Sridhar; Sahinalp, Cenk; Ruppin, Eytan.
Afiliación
  • Jiang P; Cancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA. peng.jiang@nih.gov.
  • Sinha S; Cancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
  • Aldape K; Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
  • Hannenhalli S; Cancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
  • Sahinalp C; Cancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
  • Ruppin E; Cancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA. eytan.ruppin@nih.gov.
Nat Rev Cancer ; 22(11): 625-639, 2022 11.
Article en En | MEDLINE | ID: mdl-36064595
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.
Asunto(s)

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Investigación Biomédica / Neoplasias Límite: Humans Idioma: En Revista: Nat Rev Cancer Asunto de la revista: NEOPLASIAS Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Investigación Biomédica / Neoplasias Límite: Humans Idioma: En Revista: Nat Rev Cancer Asunto de la revista: NEOPLASIAS Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos