The DOI matches its Crossref record; 63 of the 63 references it cites were found in a registry or an index.
Applications of Support Vector Machine (SVM) Learning in Cancer Genomics
Open accessAbstract
Machine learning with maximization (support) of separating margin (vector), called support vector machine (SVM) learning, is a powerful classification tool that has been used for cancer genomic classification or subtyping. Today, as advancements in high-throughput technologies lead to production of large amounts of genomic and epigenomic data, the classification feature of SVMs is expanding its use in cancer genomics, leading to the discovery of new biomarkers, new drug targets, and a better understanding of cancer driver genes. Herein we reviewed the recent progress of SVMs in cancer genomic studies. We intend to comprehend the strength of the SVM learning and its future perspective in cancer genomic applications.
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Cites
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Cited by
Ahmed, Z., Mohamed, K., Zeeshan, S., & Dong, X. (2020) · Database · doi:10.1093/database/baaa010 · Cited by 1,035
RETRACTED ARTICLE: Artificial intelligence and machine learning in precision and genomic medicine
Quazi, S. (2022) · Medical Oncology · doi:10.1007/s12032-022-01711-1 · Cited by 432
RetractedKufel, J., Bargieł-Łączek, K., Kocot, S., Koźlik, M., Bartnikowska, W., Janik, M., Czogalik, Ł., Dudek, P., Magiera, M., Lis, A., et al. (2023) · Diagnostics · doi:10.3390/diagnostics13152582 · Cited by 394
Early lung cancer diagnostic biomarker discovery by machine learning methods
Xie, Y., Meng, W.-Y., Li, R.-Z., Wang, Y.-W., Qian, X., Chan, C., Yu, Z.-F., Fan, X.-X., Pan, H.-D., Xie, C., et al. (2021) · Translational Oncology · doi:10.1016/j.tranon.2020.100907 · Cited by 269
He, S., Leanse, L. G., & Feng, Y. (2021) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2021.113922 · Cited by 141
Metadata
- Venue
- Cancer Genomics & Proteomics
- Published
- 2018-01-02
- Volume
- 15
- Issue
- 1
- Pages
- 41-51
- ISSN
- 1109-6535 (ISSN-L)
- 1790-6245
- OpenAlex
- W2778455075
- Cited by
- 1,528
- References
- 63
- FWCI
- 27.55
- Type
- journal article
- Language
- en
- Open access
- diamond
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
