The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
A review of feature selection techniques in bioinformatics
Open accessAbstract
Feature selection techniques have become an apparent need in many bioinformatics applications. In addition to the large pool of techniques that have already been developed in the machine learning and data mining fields, specific applications in bioinformatics have led to a wealth of newly proposed techniques. In this article, we make the interested reader aware of the possibilities of feature selection, providing a basic taxonomy of feature selection techniques, and discussing their use, variety and potential in a number of both common as well as upcoming bioinformatics applications. Contact: yvan.saeys@psb.ugent.be Supplementary information: http://bioinformatics.psb.ugent.be/supplementary_data/yvsae/fsreview
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Smyth, G. K. (2004) · Statistical Applications in Genetics and Molecular Biology · doi:10.2202/1544-6115.1027 · Cited by 11,829
Gene selection for cancer classification using support vector machines
Guyon, I., Weston, J., Barnhill, S., & Vapnik, V. (2002) · Machine Learning · doi:10.1023/a:1012487302797 · Cited by 9,954
The Structure of Haplotype Blocks in the Human Genome
Gabriel, S. B., Schaffner, S. F., Nguyen, H., Moore, J. M., Roy, J., Blumenstiel, B., Higgins, J., DeFelice, M., Lochner, A., Faggart, M., et al. (2002) · Science · doi:10.1126/science.1069424 · Cited by 5,863
Use of proteomic patterns in serum to identify ovarian cancer
Petricoin, E. F., Ardekani, A. M., Hitt, B. A., Levine, P. J., Fusaro, V. A., Steinberg, S. M., Mills, G. B., Simone, C., Fishman, D. A., Kohn, E. C., et al. (2002) · The Lancet · doi:10.1016/s0140-6736(02)07746-2 · Cited by 3,236
Cited by
Feature Selection: A Data Perspective
Li, J., Cheng, K., Wang, S., Morstatter, F., Trevino, R. P., Tang, J., & Liu, H. (2018) · ACM Computing Surveys · doi:10.1145/3136625 · Cited by 2,442
Learning from class-imbalanced data: Review of methods and applications
Haixiang, G., Yijing, L., Shang, J., Mingyun, G., Yuanyue, H., & Bing, G. (2017) · Expert Systems with Applications · doi:10.1016/j.eswa.2016.12.035 · Cited by 2,377
Inferring Regulatory Networks from Expression Data Using Tree-Based Methods
Huynh-Thu, V. A., Irrthum, A., Wehenkel, L., & Geurts, P. (2010) · PLoS ONE · doi:10.1371/journal.pone.0012776 · Cited by 2,131
Machine learning algorithm validation with a limited sample size
Vabalas, A., Gowen, E., Poliakoff, E., & Casson, A. J. (2019) · PLOS ONE · doi:10.1371/journal.pone.0224365 · Cited by 1,901
Machine learning for medical imaging
Erickson, B. J., Korfiatis, P., Akkus, Z., & Kline, T. L. (2017) · RadioGraphics · doi:10.1148/rg.2017160130 · Cited by 1,672
Metadata
- Authors
- Saeys, Y., Inza, I., & Larrañaga, P.
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2007-08-24
- Volume
- 23
- Issue
- 19
- Pages
- 2507-2517
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- OpenAlex
- W2119387367
- Cited by
- 5,244
- References
- 4
- FWCI
- 37.95
- Type
- journal article
- Language
- en
- Open access
- green
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