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3. ELIXIR and Toxicology: a community in development [version 2; peer review: 2 approved]

8. CoMPARA: Collaborative Modeling Project for Androgen Receptor Activity

9. QSAR modeling and chemical space analysis of antimalarial compounds

10. QSAR modeling1. and chemical space analysis of antimalarial compounds

11. Public (Q)SAR Services, Integrated Modeling Environments, and Model Repositories on the Web: State of the Art and Perspectives for Future Development

13. UNICORE – a middleware for Life Sciences grids

15. UNICORE – a middleware for Life Sciences grids

18. Description of the electronic structure of organic chemicals using semiempirical and ab initio methods for development of toxicological QSARs

24. Description of the Electronic Structure of Organic Chemicals Using Semiempirical and Ab Initio Methods for Development of Toxicological QSARs

25. QSPR Treatment of the Soil Sorption Coefficients of Organic Pollutants

26. General and Class Specific Models for Prediction of Soil Sorption Using Various Physicochemical Descriptors

27. Theoretical Descriptors for the Correlation of Aquatic Toxicity of Environmental Pollutants by Quantitative Structure-Toxicity Relationships

28. Perspective on the Relationship between Melting Points and Chemical Structure

29. Interpretation of Quantitative Structure−Property and −Activity Relationships

30. Correlation of the Solubilities of Gases and Vapors in Methanol and Ethanol with Their Molecular Structures

32. Prediction of Melting Points for the Substituted Benzenes:  A QSPR Approach

35. Public (Q)SAR Services, Integrated Modeling Environments, and Model Repositories on the Web: State of the Art and Perspectives for Future Development

36. QSAR modeling and chemical space analysis of antimalarial compounds

37. Public (Q)SAR Services, Integrated Modeling Environments, and Model Repositories on the Web: State of the Art and Perspectives for Future Development

38. QSAR modeling and chemical space analysis of antimalarial compounds

41. CoMPARA: Collaborative Modeling Project for Androgen Receptor Activity

42. Predictive Modeling of Pesticides Reproductive Toxicity in Earthworms Using Interpretable Machine-Learning Techniques on Imbalanced Data.

43. Exploring the Influence of Ionic Liquid Anion Structure on Gas-Ionic Liquid Partition Coefficients of Organic Solutes Using Machine Learning.

44. Nanomaterial Texture-Based Machine Learning of Ciprofloxacin Adsorption on Nanoporous Carbon.

45. Data-Driven Modelling of Substituted Pyrimidine and Uracil-Based Derivatives Validated with Newly Synthesized and Antiproliferative Evaluated Compounds.

46. Pesticide effect on earthworm lethality via interpretable machine learning.

47. Interpretable machine learning for the identification of estrogen receptor agonists, antagonists, and binders.

48. ELIXIR and Toxicology: a community in development.

49. Intrinsic Aqueous Solubility: Mechanistically Transparent Data-Driven Modeling of Drug Substances.

50. Machine Learning Quantitative Structure-Property Relationships as a Function of Ionic Liquid Cations for the Gas-Ionic Liquid Partition Coefficient of Hydrocarbons.

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