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Statistical Modelling of Molecular Descriptors in QSAR/QSPR. Quantitative and Network Biology (VCH)

  • ID: 2183279
  • Book
  • February 2012
  • 456 Pages
  • John Wiley and Sons Ltd
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This handbook and ready reference presents a combination of statistical, information–theoretic, and data analysis methods to meet the challenge of designing empirical models involving molecular descriptors within bioinformatics. The topics range from investigating information processing in chemical and biological networks to studying statistical and information–theoretic techniques for analyzing chemical structures to employing data analysis and machine learning techniques for QSAR/QSPR.

The high–profile international author and editor team ensures excellent coverage of the topic, making this a must–have for everyone working in chemoinformatics and structure–oriented drug design.

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Current Modeling Methods used in QSAR/QSPR (Liew Chin Yee and Yap Chun Wei)

Developing Best Practices for Descriptor–Based Property Prediction: Appropriate Matching of Datasets, Descriptors, Methods, and Expectations (Michael Krein, Tao–wei Huang, Lisa Morkowchuk, Dimitris K. Agrafiotis, and Curt M. Breneman)

Mold Molecular Descriptors for QSAR (Huixiao Hong, Svetoslav Slavov, Weigong Ge, Feng Qian, Zhenqiang Su, Hong Fang, Yiyu Cheng, Roger Perkins, Leming Shi and Weida Tong)

Multivariate Analysis of Molecular Descriptors (Viviana Consonni and Roberto Todeschini)

Partial Order Ranking and Linear Modeling: Their Use in Predictive QSAR/QSPR Studies (Andrew G. Mercader, Eduardo A. Castro)

Graph–theoretical Descriptors for Branched Polymers (Koh–hei Nitta)

Structural Similarity based Approaches for the Development of Clustering and QSPR/QSAR Models in Chemical Databases (Irene Luque Ruiz, Gonzalo Cerruela García and Miguel Ángel Gómez–Nieto)

Statistical Methods for Predicting Compound Recovery Rates for Ligand–based Virtual Screening and Assessing the Probability of Activity (Martin Vogt and Jürgen Bajorath)

Molecular Descriptors and the Electronic Structure (Horst Bögel)

New types of Descriptors and Models in QSAR/QSPR (Christian Kramer and Timothy Clark)

Consensus Models of Activity Landscapes (José L. Medina–Franco, Austin B. Yongye and Fabian López–Vallejo)

Reverse Engineering Chemical Reaction Networks from Time Series Data (Dominic P. Searson, Mark J. Willis and Allen Wright)

Reduction of Dimensionality, Order and Classification in Spaces of Theoretical Descriptions of Molecules. An Approach based on Metrics, Pattern Recognition Techniques and Graph Theoretic Considerations (George Maroulis)

The Analysis of Organic Reaction Pathways by Brownian Processing (Daniel J. Graham)

Generation of Chemical Transformations –

Reaction Pathways Prediction and Synthesis Design (Grazyna Nowak and Grzegorz Fic)
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In summary, Statistical Modelling of Molecular Descriptors in QSAR/QSPR" is a valuable treatise, aimed at practitioners, useful both for beginners and experts. It should be a must for any decent science library.   (Match, 1 November 2012)

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