Zang, Qingda <br/><br/>
Binary classification of a large collection of environmental chemicals from estrogen receptor assays by quantitative structure-activity relationship and machine learning methods.  [electronic resource] 

 -  Journal of chemical information and modeling  Dec 2013 
 - 3244-61 p.  digital 
<br/><br/> Publication Type: Journal Article; Research Support, Non-U.S. Gov't 
<br/><br/><label>ISSN: </label>1549-960X 
<br/><br/><label>Standard No.: </label>10.1021/ci400527b  doi 
<br/><br/><label>Subjects--Topical Terms: </label><br/>Algorithms<br/>Artificial Intelligence<br/>Discriminant Analysis<br/>Endocrine Disruptors--classification<br/>Environmental Monitoring<br/>High-Throughput Screening Assays<br/>Humans<br/>Quantitative Structure-Activity Relationship<br/>Receptors, Estrogen--agonists<br/>Risk Assessment<br/>Water Pollutants, Chemical--classification