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Daniel P Russo

Showing results (11-20 of 44) with videos related to

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ALTEX|February 11, 2016
Analysis of publically available skin sensitization data from REACH registrations 2008-2014Thomas Luechtefeld, Alexandra Maertens, Daniel P Russo, et al.
Analytical Chemistry|September 24, 2020
Virtual Molecular Projections and Convolutional Neural Networks for the End-to-End Modeling of Nanoparticle Activities and PropertiesDaniel P Russo, Xiliang Yan, Sunil Shende, et al.
ALTEX|February 11, 2016
Analysis of public oral toxicity data from REACH registrations 2008-2014Thomas Luechtefeld, Alexandra Maertens, Daniel P Russo, et al.
ALTEX|February 11, 2016
Global analysis of publicly available safety data for 9,801 substances registered under REACH from 2008-2014Thomas Luechtefeld, Alexandra Maertens, Daniel P Russo, et al.
Molecular Pharmaceutics|August 18, 2018
Comparing Multiple Machine Learning Algorithms and Metrics for Estrogen Receptor Binding PredictionDaniel P Russo, Kimberley M Zorn, Alex M Clark, et al.
Environmental Science & Technology|January 13, 2026
Hierarchical Mechanistic Modeling of Complex Toxicity Endpoints from Public Concentration-Response DataElena Chung, Daniel P Russo, Lauren M Aleksunes, et al.
Environmental Science & Technology|July 26, 2021
Revealing Adverse Outcome Pathways from Public High-Throughput Screening Data to Evaluate New Toxicants by a Knowledge-Based Deep Neural Network ApproachHeather L Ciallella, Daniel P Russo, Lauren M Aleksunes, et al.
American Journal of Otolaryngology|November 17, 2020
Viral markers in nasopharyngeal carcinoma: A systematic review and meta-analysis on the detection of p16<sup>INK4a</sup>, human papillomavirus (HPV), and Ebstein-Barr virus (EBV)Tristan Tham, Rosalie Machado, Daniel P Russo, et al.
Biorxiv : the Preprint Server for Biology|March 18, 2026
vToxiNet: a biologically constrained deep learning framework for interpretable prediction of drug-induced hepatotoxicityXuelian Jia, Tong Wang, Daniel P Russo, et al.
Laboratory Investigation; a Journal of Technical Methods and Pathology|August 12, 2020
Predictive modeling of estrogen receptor agonism, antagonism, and binding activities using machine- and deep-learning approachesHeather L Ciallella, Daniel P Russo, Lauren M Aleksunes, et al.
Pageof 5

Showing results (11-20 of 44) with videos related to

Sort By:
Pageof 5
ALTEX|February 11, 2016
Analysis of publically available skin sensitization data from REACH registrations 2008-2014Thomas Luechtefeld, Alexandra Maertens, Daniel P Russo, et al.
Analytical Chemistry|September 24, 2020
Virtual Molecular Projections and Convolutional Neural Networks for the End-to-End Modeling of Nanoparticle Activities and PropertiesDaniel P Russo, Xiliang Yan, Sunil Shende, et al.
ALTEX|February 11, 2016
Analysis of public oral toxicity data from REACH registrations 2008-2014Thomas Luechtefeld, Alexandra Maertens, Daniel P Russo, et al.
ALTEX|February 11, 2016
Global analysis of publicly available safety data for 9,801 substances registered under REACH from 2008-2014Thomas Luechtefeld, Alexandra Maertens, Daniel P Russo, et al.
Molecular Pharmaceutics|August 18, 2018
Comparing Multiple Machine Learning Algorithms and Metrics for Estrogen Receptor Binding PredictionDaniel P Russo, Kimberley M Zorn, Alex M Clark, et al.
Environmental Science & Technology|January 13, 2026
Hierarchical Mechanistic Modeling of Complex Toxicity Endpoints from Public Concentration-Response DataElena Chung, Daniel P Russo, Lauren M Aleksunes, et al.
Environmental Science & Technology|July 26, 2021
Revealing Adverse Outcome Pathways from Public High-Throughput Screening Data to Evaluate New Toxicants by a Knowledge-Based Deep Neural Network ApproachHeather L Ciallella, Daniel P Russo, Lauren M Aleksunes, et al.
American Journal of Otolaryngology|November 17, 2020
Viral markers in nasopharyngeal carcinoma: A systematic review and meta-analysis on the detection of p16<sup>INK4a</sup>, human papillomavirus (HPV), and Ebstein-Barr virus (EBV)Tristan Tham, Rosalie Machado, Daniel P Russo, et al.
Biorxiv : the Preprint Server for Biology|March 18, 2026
vToxiNet: a biologically constrained deep learning framework for interpretable prediction of drug-induced hepatotoxicityXuelian Jia, Tong Wang, Daniel P Russo, et al.
Laboratory Investigation; a Journal of Technical Methods and Pathology|August 12, 2020
Predictive modeling of estrogen receptor agonism, antagonism, and binding activities using machine- and deep-learning approachesHeather L Ciallella, Daniel P Russo, Lauren M Aleksunes, et al.
Pageof 5