Dr. Kunal Roy is a Professor and Ex-Head in the Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India. He has been a recipient of Commonwealth Academic Staff Fellowship (University of Manchester, 2007) and Marie Curie International Incoming Fellowship (University of Manchester, 2013). The field of his research interest is QSAR and Molecular Modeling with application in Drug Design and Ecotoxicological Modeling. Dr. Roy has published more than 350 research articles in refereed journals (current SCOPUS h index 49). He has also coauthored two QSAR-related books, edited six QSAR books and published more than ten book chapters. Dr. Roy is a Co-Editor-in-Chief of Molecular Diversity (Springer Nature). He also serves as a member of the Editorial Boards of several International Journals.
Télécharger le livre :  Materials Informatics I

This contributed volume explores the integration of machine learning and cheminformatics within materials science, focusing on predictive modeling techniques. It begins with foundational concepts in materials informatics and cheminformatics, emphasizing quantitative...
Editeur : Springer
Parution : 2025-04-02

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252,14

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Télécharger le livre :  Materials Informatics II

This contributed volume explores the application of machine learning in predictive modeling within the fields of materials science, nanotechnology, and cheminformatics. It covers a range of topics, including electronic properties of metal nanoclusters, carbon...
Editeur : Springer
Parution : 2025-03-14

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200,44

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Télécharger le livre :  Materials Informatics III

This contributed volume focuses on the application of machine learning and cheminformatics in predictive modeling for organic materials, polymers, solvents, and energetic materials. It provides an in-depth look at how machine learning is utilized to predict key...
Editeur : Springer
Parution : 2025-03-01

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200,44

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Télécharger le livre :  q-RASAR

This brief offers an introduction to the fascinating new field of quantitative read-across structure-activity relationships (q-RASAR) as a cheminformatics modeling approach in the background of quantitative structure-activity relationships (QSAR) and read-across (RA) as...
Editeur : Springer
Parution : 2024-01-25

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52,74

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Télécharger le livre :  Cheminformatics, QSAR and Machine Learning Applications for Novel Drug Development

Cheminformatics, QSAR and Machine Learning Applications for Novel Drug Development aims at showcasing different structure-based, ligand-based, and machine learning tools currently used in drug design. It also highlights special topics of computational drug design...
Editeur : Academic Press
Parution : 2023-05-23

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200,45

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Télécharger le livre :  Chemometrics and Cheminformatics in Aquatic Toxicology

CHEMOMETRICS AND CHEMINFORMATICS IN AQUATIC TOXICOLOGY Explore chemometric and cheminformatic techniques and tools in aquatic toxicology Chemometrics and Cheminformatics in Aquatic Toxicology delivers an exploration of the existing and emerging problems of contamination...
Editeur : Wiley
Parution : 2021-12-01

Format(s) : ePub
223,61

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Télécharger le livre :  In Silico Drug Design

In Silico Drug Design: Repurposing Techniques and Methodologies explores the application of computational tools that can be utilized for this approach. The book covers theoretical background and methodologies of chem-bioinformatic techniques and network modeling and...
Editeur : Academic Press
Parution : 2019-02-12

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163,52

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Télécharger le livre :  Advances in QSAR Modeling

The book covers theoretical background and methodology as well as all current applications of Quantitative Structure-Activity Relationships (QSAR). Written by an international group of recognized researchers, this edited volume discusses applications of QSAR in multiple...
Editeur : Springer
Parution : 2017-05-22
Collection : Challenges and Advances in Computational Chemistry and Physics
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410,39

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Télécharger le livre :  A Primer on QSAR/QSPR Modeling

This brief goes back to basics and describes the Quantitative structure-activity/property relationships (QSARs/QSPRs) that represent predictive models derived from the application of statistical tools correlating biological activity (including therapeutic and toxic) and...
Editeur : Springer
Parution : 2015-04-11
Collection : SpringerBriefs in Molecular Science
Format(s) : ePub
63,29

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Télécharger le livre :  Understanding the Basics of QSAR for Applications in Pharmaceutical Sciences and Risk Assessment

Understanding the Basics of QSAR for Applications in Pharmaceutical Sciences and Risk Assessment describes the historical evolution of quantitative structure-activity relationship (QSAR) approaches and their fundamental principles. This book includes clear,...
Editeur : Academic Press
Parution : 2015-03-03

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75,91

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