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Mutual information can be used to measure nonlinear relationships, and it has been widely used in the construction of gene regulatory networks. However, this method cannot measure indirect regulatory relationships under the influence of multiple genes, which reduces the accuracy of inferring gene regulatory networks.<\/jats:p><\/jats:sec><jats:sec><jats:title>Approach<\/jats:title><jats:p>This work proposes a method for constructing gene regulatory networks based on mixed entropy optimizing context-related likelihood mutual information (MEOMI). First, two entropy estimators were combined to calculate the mutual information between genes. Then, distribution optimization was performed using a context-related likelihood algorithm to eliminate some indirect regulatory relationships and obtain the initial gene regulatory network. To obtain the complex interaction between genes and eliminate redundant edges in the network, the initial gene regulatory network was further optimized by calculating the conditional mutual inclusive information (CMI2) between gene pairs under the influence of multiple genes. The network was iteratively updated to reduce the impact of mutual information on the overestimation of the direct regulatory intensity.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>The experimental results show that the MEOMI method performed better than several other kinds of gene network construction methods on DREAM challenge simulated datasets (DREAM3 and DREAM5), three real Escherichia coli datasets (E.coli SOS pathway network, E.coli SOS DNA repair network and E.coli community network) and two human datasets.<\/jats:p><\/jats:sec><jats:sec><jats:title>Availability and implementation<\/jats:title><jats:p>Source code and dataset are available at https:\/\/github.com\/Dalei-Dalei\/MEOMI\/ and http:\/\/122.205.95.139\/MEOMI\/.<\/jats:p><\/jats:sec><jats:sec><jats:title>Supplementary information<\/jats:title><jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p><\/jats:sec>","DOI":"10.1093\/bioinformatics\/btac717","type":"journal-article","created":{"date-parts":[[2022,11,7]],"date-time":"2022-11-07T13:13:58Z","timestamp":1667826838000},"source":"Crossref","is-referenced-by-count":15,"title":["An approach of gene regulatory network construction using mixed entropy optimizing context-related likelihood mutual information"],"prefix":"10.1093","volume":"39","author":[{"given":"Jimeng","family":"Lei","sequence":"first","affiliation":[{"name":"National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University , Wuhan 430070, China"},{"name":"Key Laboratory of Smart Farming for Agricultural Animals, Huazhong Agricultural University , Wuhan 430070, China"},{"name":"College of Informatics, Huazhong Agricultural University , Wuhan 430070, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zongheng","family":"Cai","sequence":"additional","affiliation":[{"name":"National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University , Wuhan 430070, China"},{"name":"Key Laboratory of Smart Farming for Agricultural Animals, Huazhong Agricultural University , Wuhan 430070, China"},{"name":"College of Informatics, Huazhong Agricultural University , Wuhan 430070, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xinyi","family":"He","sequence":"additional","affiliation":[{"name":"College of Informatics, Huazhong Agricultural University , Wuhan 430070, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wanting","family":"Zheng","sequence":"additional","affiliation":[{"name":"College of Informatics, Huazhong Agricultural University , Wuhan 430070, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9165-4012","authenticated-orcid":false,"given":"Jianxiao","family":"Liu","sequence":"additional","affiliation":[{"name":"National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University , Wuhan 430070, China"},{"name":"Key Laboratory of Smart Farming for Agricultural Animals, Huazhong Agricultural University , Wuhan 430070, China"},{"name":"College of Informatics, Huazhong Agricultural University , Wuhan 430070, China"},{"name":"Hubei Key Laboratory of Agricultural Bioinformatics, Huazhong Agricultural University , Wuhan 430070, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2022,11,7]]},"reference":[{"key":"2023010107545677600_btac717-B1","doi-asserted-by":"crossref","first-page":"e92600","DOI":"10.1371\/journal.pone.0092600","article-title":"IPCA-CMI: an algorithm for inferring gene regulatory networks based on a combination of PCA-CMI and MIT score","volume":"9","author":"Aghdam","year":"2014","journal-title":"PLoS One"},{"key":"2023010107545677600_btac717-B2","doi-asserted-by":"crossref","first-page":"942","DOI":"10.1039\/C4MB00413B","article-title":"CN: a consensus algorithm for inferring gene regulatory networks using the SORDER algorithm and conditional mutual information test","volume":"11","author":"Aghdam","year":"2015","journal-title":"Mol. 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