- 인체위해한 독성 및 유독 유해화합물질의 인체위해성 예측을 위한 4천여개 이상 molecular descriptor를 이용한 딥러닝 계산독성학 (QSAR) 모델 개발

 - 다양한 기상/액상/토양 유해화학물질의 인체위해성을 빠른 시간안에 예측 가능케하는 계산독성학 QSAR모델에 기반하여 다양한 유해화학물질에 적용 가능 (화장품, 화학산업, 반도체 유독가스/화학반응 side product 등등)

- 특허 출원 준비

SungKu Heo⁺, Usman Safder⁺, ChangKyoo Yoo^*, Deep learning driven QSAR model for environmental toxicology: effects of endocrine disrupting chemicals on human health, Environmental Pollution (ISSN: 0269-7491, SCI, IF=5.7, Top 10% journal ?Environmental Sciences), Elsevier, 253(10), pp.29-38 (2019.10) (Ack:2017R1E1A1A03070713 and 19QPPW-B152307-01)

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Good morning,

I’m happy to inform you that SungKu/Usman’s paper has been accepted in Environmental Pollution Environmental Pollution(SCI, IF=5.7, Top 10% journal ?Environmental Sciences).

Congratulation for SK’s 1^st paper in SCI journal with 1^st author (Top 10% journal ).

Title: Deep learning driven QSAR model for environmental toxicology: effects of endocrine disrupting chemicals on human health
Journal: Environmental Pollution (SCI, IF=5.7,Top 10% journal)

Authors : SungKu Heo, Usman Safder, ChangKyoo Yoo