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

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書目名稱Advances in QSAR Modeling影響因子(影響力)




書目名稱Advances in QSAR Modeling影響因子(影響力)學(xué)科排名




書目名稱Advances in QSAR Modeling網(wǎng)絡(luò)公開(kāi)度




書目名稱Advances in QSAR Modeling網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書目名稱Advances in QSAR Modeling被引頻次




書目名稱Advances in QSAR Modeling被引頻次學(xué)科排名




書目名稱Advances in QSAR Modeling年度引用




書目名稱Advances in QSAR Modeling年度引用學(xué)科排名




書目名稱Advances in QSAR Modeling讀者反饋




書目名稱Advances in QSAR Modeling讀者反饋學(xué)科排名

過(guò)份艷麗

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

使殘廢

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

善變

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