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Big data in basic and translational cancer research
Open accessAbstract
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.
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“The advancement of omics data due to breakthroughs in high-throughput technologies has generated the concept of “big data” in cancer, the analysis of which necessitates large computational resources and bioinformatic algorithms [7].”
From Bioinformatics Analysis and Validation of Potential Markers Associated with Prediction and Prognosis of Gastric Cancer (2024) · cites this paper as [7]
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Metadata
- Authors
- Jiang, P., Sinha, S., Aldape, K., Hannenhalli, S., Sahinalp, C., & Ruppin, E.
- Affiliations
- National Institutes of Health (US)
- Corresponding author
- Jiang, Peng
- Ruppin, Eytan
- Venue
- Nature Reviews Cancer
- Published
- 2022-09-05
- Volume
- 22
- Issue
- 11
- Pages
- 625-639
- ISSN
- 1474-175X (ISSN-L)
- 1474-1768
- PMC
- PMC9443637
- OpenAlex
- W4294636450
- Cited by
- 254
- References
- 188
- Citations by year
- 2026: 36 · 2025: 59 · 2024: 101 · 2023: 54 · 2022: 4
- FWCI
- 6.85
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Nature reviews. Cancer (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Cancer Institute
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Science, Research, and Medicine
- Keywords
- big data, cancer research, cancer omics, data integration, bioinformatics, artificial intelligence, biomarker discovery, clinical trials, cancer treatment development, high-throughput technologies
- MeSH terms
- Artificial Intelligence, Humans, Neoplasms, Computational Biology, Biomedical Research, Proteomics, Translational Research, Biomedical
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