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Bioinformatics Research Based on Evolutionary Computation

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Association Analysis Techniques and Applications in Bioinformatics

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Abstract

Evolutionary computation-based association analysis has achieved significant progress in the field of data mining. This research approach fully leverages the advantages of evolutionary computation in global search and optimization, enhancing the efficiency and accuracy of association rule mining. The key of evolutionary computation methods lies in transforming association analysis problems into optimization problems. By doing so, the optimal association rules can be sought within the space of association rules. To achieve this objective, researchers need to define fitness functions to evaluate the quality of association rules, such as support and confidence measures. Additionally, evolutionary computation algorithms require settings for population initialization, selection, mutation, and other operations to effectively explore the search space.

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Authors and Affiliations

  1. School of Computer and Electronic Information, Guangxi University, Nanning, Guangxi, China

    Qingfeng Chen

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  1. Qingfeng Chen
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Chen, Q. (2024). Bioinformatics Research Based on Evolutionary Computation. In: Association Analysis Techniques and Applications in Bioinformatics. Springer, Singapore. https://doi.org/10.1007/978-981-99-8251-6_11

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  • DOI: https://doi.org/10.1007/978-981-99-8251-6_11

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-8250-9

  • Online ISBN: 978-981-99-8251-6

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