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Metadata Files for Structure-based QSAR models to predict repeat dose toxicity points of departure

Metadata Updated: March 29, 2021

This paper describes a model to take chemical structures and predict a property (the point of departure) for a new chemical. No new data were generated. The contents of this zip file contains metadata that you could use to make a model prediction. It does contain all of the code and a help file describing how to run the model.

This dataset is associated with the following publication: Pradeep, P., K. Paul-Friedman, and R. Judson. Structure-based QSAR Models to Predict Repeat Dose Toxicity Points of Departure. Computational Toxicology. Elsevier B.V., Amsterdam, NETHERLANDS, 16(November 2020): 100139, (2020).

Access & Use Information

Public: This dataset is intended for public access and use. License: See this page for license information.

Downloads & Resources



Metadata Created Date March 29, 2021
Metadata Updated Date March 29, 2021

Metadata Source

Harvested from EPA ScienceHub

Additional Metadata

Resource Type Dataset
Metadata Created Date March 29, 2021
Metadata Updated Date March 29, 2021
Publisher U.S. EPA Office of Research and Development (ORD)
Data Last Modified 2020-09-24
Public Access Level public
Bureau Code 020:00
Schema Version
Harvest Object Id 269a94eb-c4f1-4585-87bf-19befeceed5a
Harvest Source Id 04b59eaf-ae53-4066-93db-80f2ed0df446
Harvest Source Title EPA ScienceHub
Program Code 020:000
Publisher Hierarchy U.S. Government > U.S. Environmental Protection Agency > U.S. EPA Office of Research and Development (ORD)
Related Documents
Source Datajson Identifier True
Source Hash f25ae75724ffa058a560f406361542e003e437ce
Source Schema Version 1.1

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