Fuzzy logic based approaches for gene regulatory network inference
作者：
Highlights：
• The gene regulatory network inference (GRNI) is a well-posed problem in the field of Bioinformatics and Systems Biology. In the last 2-3 decades, fuzzy logic and it hybridization with other computational intelligence approaches has shown a wide applications in the GRNI.
• In this article, we performed a critical review of fuzzy logic and its hybrid approaches for GRNI proposed in the last 2-3 decades.
• We have also classified fuzzy based hybrid approach and performed a comparison in terms of their strength, weakness and applications.
摘要
•The gene regulatory network inference (GRNI) is a well-posed problem in the field of Bioinformatics and Systems Biology. In the last 2-3 decades, fuzzy logic and it hybridization with other computational intelligence approaches has shown a wide applications in the GRNI.•In this article, we performed a critical review of fuzzy logic and its hybrid approaches for GRNI proposed in the last 2-3 decades.•We have also classified fuzzy based hybrid approach and performed a comparison in terms of their strength, weakness and applications.
论文关键词：Fuzzy logic,Gene regulatory network,Network inference,Fuzzy clustering,Fuzzy inference system,Systems biology
论文评审过程：Received 7 May 2018, Revised 10 December 2018, Accepted 12 December 2018, Available online 17 December 2018, Version of Record 13 June 2019.
论文官网地址：https://doi.org/10.1016/j.artmed.2018.12.004
