A Machine Learning Approach to Predict Gene Regulatory Networks in Seed Development in Arabidopsis

MLA

Computer Science, et al. A Machine Learning Approach to Predict Gene Regulatory Networks in Seed Development in Arabidopsis. 2016. EBSCOhost, widgets.ebscohost.com/prod/customlink/proxify/proxify.php?count=1&encode=0&proxy=&find_1=&replace_1=&target=https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&scope=site&db=edsoai&AN=edsoai.on1199302624&authtype=sso&custid=ns315887.

APA

Computer Science, School of Plant and Environmental Sciences, Grene, R., Heath, L. S., Li, S., Collakova, E., Elmarakeby, H. A., Ni, Y., & Aghamirzaie, D. (2016). A Machine Learning Approach to Predict Gene Regulatory Networks in Seed Development in Arabidopsis.

Chicago

Computer Science, School of Plant and Environmental Sciences, Ruth Grene, Lenwood S. Heath, Song Li, Eva Collakova, Haitham A. Elmarakeby, Ying Ni, and Delasa Aghamirzaie. 2016. “A Machine Learning Approach to Predict Gene Regulatory Networks in Seed Development in Arabidopsis.” http://widgets.ebscohost.com/prod/customlink/proxify/proxify.php?count=1&encode=0&proxy=&find_1=&replace_1=&target=https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&scope=site&db=edsoai&AN=edsoai.on1199302624&authtype=sso&custid=ns315887.