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Environmental Science & Technology
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May 24, 2023
Advancing Computational Toxicology by Interpretable Machine Learning
Xuelian Jia, Tong Wang, Hao Zhu
Journal of Hazardous Materials
|
June 24, 2022
Mechanism-driven modeling of chemical hepatotoxicity using structural alerts and an in vitro screening assay
Xuelian Jia, Xia Wen, Daniel P Russo, et al.
Scientific Reports
|
June 16, 2016
A humanized anti-DLL4 antibody promotes dysfunctional angiogenesis and inhibits breast tumor growth
Xuelian Jia, Wenyi Wang, Zhuobin Xu, et al.
Biorxiv : the Preprint Server for Biology
|
March 18, 2026
vToxiNet: a biologically constrained deep learning framework for interpretable prediction of drug-induced hepatotoxicity
Xuelian Jia, Tong Wang, Daniel P Russo, et al.
Journal of Hazardous Materials
|
April 27, 2024
Hybrid non-animal modeling: A mechanistic approach to predict chemical hepatotoxicity
Elena Chung, Xia Wen, Xuelian Jia, et al.
Trends in Pharmacological Sciences
|
May 15, 2025
Developmental toxicity: artificial intelligence-powered assessments
Tong Wang, Xuelian Jia, Lauren M Aleksunes, et al.
Carbon
|
February 27, 2023
Integrating structure annotation and machine learning approaches to develop graphene toxicity models
Tong Wang, Daniel P Russo, Dimitrios Bitounis, et al.
ACS Sustainable Chemistry & Engineering
|
July 9, 2021
Construction of a Virtual Opioid Bioprofile: A Data-Driven QSAR Modeling Study to Identify New Analgesic Opioids
Xuelian Jia, Heather L Ciallella, Daniel P Russo, et al.
Nano Letters
|
August 9, 2024
An Online Nanoinformatics Platform Empowering Computational Modeling of Nanomaterials by Nanostructure Annotations and Machine Learning Toolkits
Tong Wang, Daniel P Russo, Philip Demokritou, et al.
Cancer Letters
|
January 8, 2016
MMGZ01, an anti-DLL4 monoclonal antibody, promotes nonfunctional vessels and inhibits breast tumor growth
Zhuobin Xu, Zegen Wang, Xuelian Jia, et al.
Page
of 3
Search research articles
Search
Showing results (1-10 of 22) with videos related to
Sort By:
Page
of 3
Environmental Science & Technology
|
May 24, 2023
Advancing Computational Toxicology by Interpretable Machine Learning
Xuelian Jia, Tong Wang, Hao Zhu
Journal of Hazardous Materials
|
June 24, 2022
Mechanism-driven modeling of chemical hepatotoxicity using structural alerts and an in vitro screening assay
Xuelian Jia, Xia Wen, Daniel P Russo, et al.
Scientific Reports
|
June 16, 2016
A humanized anti-DLL4 antibody promotes dysfunctional angiogenesis and inhibits breast tumor growth
Xuelian Jia, Wenyi Wang, Zhuobin Xu, et al.
Biorxiv : the Preprint Server for Biology
|
March 18, 2026
vToxiNet: a biologically constrained deep learning framework for interpretable prediction of drug-induced hepatotoxicity
Xuelian Jia, Tong Wang, Daniel P Russo, et al.
Journal of Hazardous Materials
|
April 27, 2024
Hybrid non-animal modeling: A mechanistic approach to predict chemical hepatotoxicity
Elena Chung, Xia Wen, Xuelian Jia, et al.
Trends in Pharmacological Sciences
|
May 15, 2025
Developmental toxicity: artificial intelligence-powered assessments
Tong Wang, Xuelian Jia, Lauren M Aleksunes, et al.
Carbon
|
February 27, 2023
Integrating structure annotation and machine learning approaches to develop graphene toxicity models
Tong Wang, Daniel P Russo, Dimitrios Bitounis, et al.
ACS Sustainable Chemistry & Engineering
|
July 9, 2021
Construction of a Virtual Opioid Bioprofile: A Data-Driven QSAR Modeling Study to Identify New Analgesic Opioids
Xuelian Jia, Heather L Ciallella, Daniel P Russo, et al.
Nano Letters
|
August 9, 2024
An Online Nanoinformatics Platform Empowering Computational Modeling of Nanomaterials by Nanostructure Annotations and Machine Learning Toolkits
Tong Wang, Daniel P Russo, Philip Demokritou, et al.
Cancer Letters
|
January 8, 2016
MMGZ01, an anti-DLL4 monoclonal antibody, promotes nonfunctional vessels and inhibits breast tumor growth
Zhuobin Xu, Zegen Wang, Xuelian Jia, et al.
Page
of 3