Titlebook: Advances in QSAR Modeling; Applications in Phar Kunal Roy Book 2017 Springer International Publishing AG 2017 Quantitative Structure-Activi

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书目名称Advances in QSAR Modeling影响因子(影响力)




书目名称Advances in QSAR Modeling影响因子(影响力)学科排名




书目名称Advances in QSAR Modeling网络公开度




书目名称Advances in QSAR Modeling网络公开度学科排名




书目名称Advances in QSAR Modeling被引频次




书目名称Advances in QSAR Modeling被引频次学科排名




书目名称Advances in QSAR Modeling年度引用




书目名称Advances in QSAR Modeling年度引用学科排名




书目名称Advances in QSAR Modeling读者反馈




书目名称Advances in QSAR Modeling读者反馈学科排名

过份艳丽

The Maximum Common Substructure (MCS) Search as a New Tool for SAR and QSARres of this software are: (I) the process of the MCSs between two molecules represented as graphs and (II) the detection and the graphical representation of the dissimilar substructures that are identified in the target and the source molecules. The user may consequently quantify the properties and

使残废

Generative Topographic Mapping Approach to Chemical Space Analysisitial molecular descriptors and user-defined mapping parameters. This multi-purpose “Swiss army knife” of dimensionality reduction may furthermore extract “privileged” structural patterns associated to bioactivities of interest, and hence contribute to an intuitive understanding of structure-activit

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morale

Quantitative Structure-Epigenetic Activity Relationshipsactivity cliff generators and their relevance to develop QSAR models. Computational methods applied to elucidate Quantitative Structure-Epigenetic Activity Relationships are in line with the increasing and developing research area of Epi-informatics.

urethritis

QSAR/QSPR Modeling in the Design of Drug Candidates with Balanced Pharmacodynamic and Pharmacokinetiroaches, for in vitro permeability predictions, predictions for human intestinal absorption and blood brain barrier penetration, as well as for plasma protein binding and drug metabolism. The value of global and local models as well as their interpretability and the criteria for their evaluation and

善变

Strategy for Identification of Nanomaterials’ Critical Properties Linked to Biological Impacts: Inteal systems . is central, in order to enable both prediction of impacts from related NMs [via quantitative property-activity or structure-activity relationships (QPARs/QSARs)] and development of strategies to ensure that these features are avoided in NM production in the future (“safety by design”).

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Counter-Propagation Artificial Neural Network Models for Prediction of Carcinogenicity of Non-congen. CP ANN algorithm represents a suitable tool for modeling of complex biological data like carcinogenicity. We emphasized on the representation of key development steps needed to be involved in model construction to meet requirement of five OECD principles. First of all, it reported the description