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Quantitative Toxicity Prediction Using Topology Based Multitask Deep Neural Networks 원문보기

Journal of chemical information and modeling, v.58 no.2, 2018년, pp.520 - 531  

Wu, Kedi ,  Wei, Guo-Wei

Abstract AI-Helper 아이콘AI-Helper

The understanding of toxicity is of paramount importance to human health and environmental protection. Quantitative toxicity analysis has become a new standard in the field. This work introduces element specific persistent homology (ESPH), an algebraic topology approach, for quantitative toxicity pr...

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