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65th Annual Meeting of the German Association for Medical Informatics, Biometry and Epidemiology (GMDS), Meeting of the Central European Network (CEN: German Region, Austro-Swiss Region and Polish Region) of the International Biometric Society (IBS)

06.09. - 09.09.2020, Berlin (online conference)

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Biological Domain Knowledge Based Feature Selection, Applied on Gene Expression Data

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  • Malik Yousef - Zefat Academic College, Department of Information System, Zefat, Israel

Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie. 65th Annual Meeting of the German Association for Medical Informatics, Biometry and Epidemiology (GMDS), Meeting of the Central European Network (CEN: German Region, Austro-Swiss Region and Polish Region) of the International Biometric Society (IBS). Berlin, 06.-09.09.2020. Düsseldorf: German Medical Science GMS Publishing House; 2021. DocAbstr. 500

doi: 10.3205/20gmds085, urn:nbn:de:0183-20gmds0851

Published: February 26, 2021

© 2021 Yousef.
This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 License. See license information at http://creativecommons.org/licenses/by/4.0/.

Outline

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In biological data analysis, most of the computational feature selection methodologies (that use machine learning) were taken from other fields, without considering the nature of the biological data. In this talk, we review existing feature ranking and feature selection approaches that are based on the biological knowledge. One of the goals of the current talk is to encourage the bioinformatics community to reconsider how feature selection in biological datasets can benefit from the effective use of the biological and biomedical relationships of the features during the selection process.

I will present our related works in this topic as such SVM-RCE, SVM-RNE, and maTE.

The authors declare that they have no competing interests.

The authors declare that an ethics committee vote is not required.