Fw: IJQSPR Special Issue on "Predictive Capabilities of QSAR and QSPR Models"

[Kunal Roy]

IJQSPR Special Issue on "Predictive Capabilities of QSAR and QSPR Models"

Guest Editor: Dr. Emili Besalu, University of Girona, Spain

Call for Papers: http://www.igi-global.com/calls-for-papers-special/international-journal-quantitative-structure-property/126552

Submission Due Date
7/1/2016

Guest Editors
Emili Besalú, University of Girona, Catalonia, Spain

Introduction
The scope of this special issue, being wide, embraces the topic of discussing the real predictive capabilities of QSAR/QSPR models (linear, non-linear, classifiers, ranking-based,...) or inverse QSAR tools. It is encouraged to discuss, among others, the quality and scope of the predictions, the utility of cross-validation techniques, randomization tests analysis, or practical/ theoretical discussions around models and its effectiveness.

Objective
The objective of this special issue is to focus on the predictive model capabilities, an aspect that many times is overlooked after a more or less complicated model has been obtained. In order to improve model quality, authors are expected to present them according to the existing standard of the QSPR field but also putting special attention on discussions around the concept of the model predictive capacities and robustness. This would demand the model to be accompanied with a discussion on several statistical parameters or cross-validation algorithmic results. Theoretical developments are also welcome, and as well as discussions on a special issue related concept.

Recommended Topics
Topics to be discussed in this special issue include (but are not limited to) the following:

• Predictive QSAR, QSPR, QSTR models
• Linear models
• Non-linear models (classifiers, ranks, neural networks, trees, support vector machines, etc.)
• Inverse QSAR tools
• Cross-validation techniques (leave-one-out, leave-many-out, n-fold, etc.)
• Randomization test procedures
• Jackknife procedures
• Bootstrapping
• Statistical parameters (r2, q2, etc.)
• QSAR pitfalls
• Range of model application
• Outliers
• Data pre-treatment
• Variables selection
• Training, Test, Validation and External sets

Submission Procedure
Researchers and practitioners are invited to submit papers for this special theme issue on Predictive Capabilities of QSAR and QSPR Models on or before July 1st 2016. All submissions must be original and may not be under review by another publication. INTERESTED AUTHORS SHOULD CONSULT THE JOURNAL’S GUIDELINES FOR MANUSCRIPT SUBMISSIONS at http://www.igi-global.com/publish/contributor-resources/before-you-write/. All submitted papers will be reviewed on a double-blind, peer review basis. Papers must follow APA style for reference citations.

All submissions and inquiries should be directed to the attention of:
Emili Besalú
Guest Editor 
International Journal of Quantitative Structure-Property Relationships (IJQSPR)
E-mail: emili....@udg.edu

Submit a Manuscript to: Predictive Capabilities o...

 

Prof. Kunal Roy, Ph.D.
Professor, Drug Theoretics and Cheminformatics Lab, Department of Pharmaceutical Technology,
JADAVPUR UNIVERSITY, Kolkata 700 032 (INDIA)

Email : kr...@pharma.jdvu.ac.in , kunal...@yahoo.com  ; Phone: +91 33 2457 2051 (Off)

URL :   http://sites.google.com/site/kunalroyindia/, http://www.jaduniv.edu.in/profile.php?uid=550

Publication list: http://www.researcherid.com/rid/B-1673-2009  

ORCID: http://orcid.org/0000-0003-4486-8074

Formerly, Marie Curie International Incoming Fellow and Commonwealth Academic Staff Fellow, University of Manchester, UK

[Kunal Roy]