A multi-objective gene clustering algorithm guided by apriori biological knowledge with intensification and diversification strategies

Author:

Parraga-Alava Jorge,Dorn Marcio,Inostroza-Ponta MarioORCID

Funder

Secretaría de Educación Superior, Ciencia, Tecnología e Innovación

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

DICYT-USACH

Publisher

Springer Science and Business Media LLC

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Genetics,Molecular Biology,Biochemistry

Cited by 18 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. The Application of Big Data in the Management of Ideological and Political Education in the Development of Education Network;International Journal of Web-Based Learning and Teaching Technologies;2024-08-05

2. Advancing Gene Expression Data Analysis: an Innovative Multi-objective Optimization Algorithm for Simultaneous Feature Selection and Clustering;Brazilian Archives of Biology and Technology;2024

3. Evaluating the incorporation of Biological Knowledge in multiobjective clustering of gene expression data;2023 42nd IEEE International Conference of the Chilean Computer Science Society (SCCC);2023-10-23

4. Improving solution diversity on NSGA-II for multi-objective clustering problems;2022 41st International Conference of the Chilean Computer Science Society (SCCC);2022-11-21

5. Definition of the molecular bases of cold and hot properties of traditional Chinese medicine through machine learning;Pharmacological Research - Modern Chinese Medicine;2022-09

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