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4. eTRANSAFE: data science to empower translational safety assessment

8. Utilizing Omics Data for Chemical Grouping.

9. 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.

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

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

20. A Study on Feature Selection for Toxicity Prediction

21. Using kNN Model for Automatic Feature Selection

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

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

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

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

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

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

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

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

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