Development of Adverse Outcome Pathway for PPARγ Antagonism Leading to Pulmonary Fibrosis and Chemical Selection for Its Validation: ToxCast Database and a Deep Learning Artificial Neural Network Model-Based Approach

MLA

Lyle D. Burgoon, et al. “Development of Adverse Outcome Pathway for PPARγ Antagonism Leading to Pulmonary Fibrosis and Chemical Selection for Its Validation: ToxCast Database and a Deep Learning Artificial Neural Network Model-Based Approach.” Chemical Research in Toxicology, vol. 32, May 2019, pp. 1212–22. 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=edsair&AN=edsair.doi.dedup.....d0f5989fd1b529be368cc1b3a71dc5d8&authtype=sso&custid=ns315887.

APA

Lyle D. Burgoon, Changheon Kim, Taehyun Park, Jinhee Choi, Edward J. Perkins, Jaeseong Jeong, Ji-Yeon Roh, & Natàlia Garcia-Reyero. (2019). Development of Adverse Outcome Pathway for PPARγ Antagonism Leading to Pulmonary Fibrosis and Chemical Selection for Its Validation: ToxCast Database and a Deep Learning Artificial Neural Network Model-Based Approach. Chemical Research in Toxicology, 32, 1212–1222.

Chicago

Lyle D. Burgoon, Changheon Kim, Taehyun Park, Jinhee Choi, Edward J. Perkins, Jaeseong Jeong, Ji-Yeon Roh, and Natàlia Garcia-Reyero. 2019. “Development of Adverse Outcome Pathway for PPARγ Antagonism Leading to Pulmonary Fibrosis and Chemical Selection for Its Validation: ToxCast Database and a Deep Learning Artificial Neural Network Model-Based Approach.” Chemical Research in Toxicology 32 (May): 1212–22. 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=edsair&AN=edsair.doi.dedup.....d0f5989fd1b529be368cc1b3a71dc5d8&authtype=sso&custid=ns315887.