The DOI matches its Crossref record; 119 of the 119 references it cites were found in a registry or an index.
Feature selection methods for big data bioinformatics: A survey from the search perspective
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Citations
Cites
Breiman, L. (2001) · Machine Learning · doi:10.1023/a:1010933404324 · Cited by 133,538
Cortes, C., & Vapnik, V. (1995) · Machine Learning · doi:10.1007/bf00994018 · Cited by 59,421
Kennedy, J., & Eberhart, R. (2002) · Proceedings of ICNN'95 - International Conference on Neural Networks · doi:10.1109/icnn.1995.488968 · Cited by 58,192
Holland, J. H. (1992) · The MIT Press eBooks · doi:10.7551/mitpress/1090.001.0001 · Cited by 47,002
Optimization by Simulated Annealing
Kirkpatrick, S., Gelatt, C. D., & Vecchi, M. P. (1983) · Science · doi:10.1126/science.220.4598.671 · Cited by 45,134
Regularization and Variable Selection Via the Elastic Net
Zou, H., & Hastie, T. (2005) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.1467-9868.2005.00503.x · Cited by 20,957
Pawlak, Z. (1982) · International Journal of Computer & Information Sciences · doi:10.1007/bf01001956 · Cited by 12,322
Golub, T. R., Slonim, D. K., Tamayo, P., Huard, C., Gaasenbeek, M., Mesirov, J. P., Coller, H., Loh, M. L., Downing, J. R., Caligiuri, M. A., et al. (1999) · Science · doi:10.1126/science.286.5439.531 · Cited by 11,516
In silico prediction of protein-protein interactions in human macrophages
Souiai, O., Guerfali, F., Ben Miled, S., Brun, C., & Benkahla, A. (2014) · BMC Research Notes · doi:10.1186/1756-0500-7-157 · Cited by 10,803
Significance analysis of microarrays applied to the ionizing radiation response
Tusher, V. G., Tibshirani, R., & Chu, G. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.091062498 · Cited by 10,568
Cited by
Tyralis, H., Papacharalampous, G., & Langousis, A. (2019) · Water · doi:10.3390/w11050910 · Cited by 771
Machine learning and integrative analysis of biomedical big data
Mirza, B., Wang, W., Wang, J., Choi, H., Chung, N. C., & Ping, P. (2019) · Genes · doi:10.3390/genes10020087 · Cited by 380
Data Integration Challenges for Machine Learning in Precision Medicine
Martínez-García, M., & Hernández-Lemus, E. (2022) · Frontiers in Medicine · doi:10.3389/fmed.2021.784455 · Cited by 185
Lessons and tips for designing a machine learning study using EHR data
Arbet, J., Brokamp, C., Meinzen-Derr, J., Trinkley, K. E., & Spratt, H. M. (2021) · Journal of Clinical and Translational Science · doi:10.1017/cts.2020.513 · Cited by 46
Metadata
- Authors
- Wang, L., Wang, Y., & Chang, Q.
- Venue
- Methods
- Publisher
- Elsevier BV
- Published
- 2016-12
- Volume
- 111
- Pages
- 21-31
- ISSN
- 1046-2023 (ISSN-L)
- OpenAlex
- W2516938563
- Cited by
- 331
- References
- 119
- FWCI
- 14.90
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Feature selection methods for big data bioinformatics: A survey from the search perspective. https://app.cochat.ai/papers/10.1016/j.ymeth.2016.08.014
- The paper
- Wang, L., Wang, Y., & Chang, Q. (2016). Feature selection methods for big data bioinformatics: A survey from the search perspective. Methods. https://doi.org/10.1016/j.ymeth.2016.08.014
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.
