Machine learning study of the extended drug–target interaction network informed by pain related voltage-gated sodium channels

aResearch Center of Nonlinear Science, School of Mathematical and Physical Sciences, Wuhan Textile University, Wuhan, P R. China

bDepartment of Mathematics, Michigan State University, East Lansing, MI, United States

cKey Laboratory of Computational Mathematics, Guangdong Province, and School of Mathematics, Sun Yat-sen University, Guangzhou, P R. China

Departments of dElectrical and Computer Engineering and

eBiochemistry and Molecular Biology, Michigan State University, East Lansing, MI, United States

*Corresponding author. Address: Department of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States. Tel.: +01-517-353-4689. E-mail address: [email protected] (G. W. Wei).

Sponsorships or competing interests that may be relevant to content are disclosed at the end of this article.

Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal's Web site (www.painjournalonline.com).

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