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4. eTRANSAFE: data science to empower translational safety assessment

7. Utilizing Omics Data for Chemical Grouping.

8. Molecular similarity in chemical informatics and predictive toxicity modeling: from quantitative read-across (q-RA) to quantitative read-across structure–activity relationship (q-RASAR) with the application of machine learning.

13. Construction of an In Silico Structural Profiling Tool Facilitating Mechanistically Grounded Classification of Aquatic Toxicants

15. Quantitative structure-activity relationships of comparative toxicity to aquatic organisms

19. A Study on Feature Selection for Toxicity Prediction

20. Using kNN Model for Automatic Feature Selection

25. Statement on advancing the assessment of chemical mixtures and their risks for human health and the environment

26. Internationalization of read-across as a validated new approach method (NAM) for regulatory toxicology

36. Optimizing drug discovery by Investigative Toxicology: Current and future trends

37. Optimizing drug discovery by Investigative Toxicology: Current and future trends

38. Statement on advancing the assessment of chemical mixtures and their risks for human health and the environment

47. Exploring the Potential of ToxCast Data in Supporting Read-Across for Evaluation of Food Chemical Safety

48. A Robust, Mechanistically Based In SilicoStructural Profiler for Hepatic Cholestasis

49. Legacy data sharing to improve drug safety assessment: the eTOX project

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