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Bayesian Classifiers for Chemical Toxicity Prediction
2011
2011 IEEE International Conference on Bioinformatics and Biomedicine
A major concern across the globe is the growing number of new chemicals that are brought to use on a regular basis without having any knowledge about their toxic behavior. The challenge here is that the growth in the number of chemicals is fast, and the traditional standards for toxicity testing involve a slow and expensive process of in vivo animal testing. Hence, a number of attempts are being made to find alternate methods of toxicity testing. In this paper we explore Bayesian classifiers
doi:10.1109/bibm.2011.109
dblp:conf/bibm/MishraPH11
fatcat:5f3s6f37erfqhe54n3f7cwwrwa