Current Landscape of Hierarchical QSAR Modeling and its Applications: Some Comments on the Importance of Mathematical Descriptors as well as Rigorous Statistical Methods of Model Building and Validation

Subhash C. Basak; Subhabrata Majumdar

doi:10.1016/B978-1-68108-198-4.50011-4

Current Landscape of Hierarchical QSAR Modeling and its Applications: Some Comments on the Importance of Mathematical Descriptors as well as Rigorous Statistical Methods of Model Building and Validation

Subhash C. Basak, Subhabrata Majumdar

Natural Resources Research Institute

Research output: Chapter in Book/Report/Conference proceeding › Chapter

5 Scopus citations

Abstract

Mathematical chemistry or more accurately discrete mathematical chemistry had a tremendous growth spurt in the second half of the twentieth century and the same trend is continuing in the twenty first century. This continual growth was fueled primarily by two major factors: 1) Novel applications of discrete mathematical concepts to chemical and biological systems, and 2) Availability of high speed computers and relevant software whereby hypothesis driven as well as discovery oriented research on large data sets could be carried out. This led to the development of not only a plethora of new concepts, but also to various useful applications. This chapter will discuss the major milestones in the development of hierarchical QSARs for the prediction of physical as well as biological properties of various classes of chemicals by the Basak group of researchers using mathematical descriptors and different statistical methods.

Original language	English (US)
Title of host publication	Advances in Mathematical Chemistry and Applications
Subtitle of host publication	Revised Edition
Publisher	Elsevier Inc.
Pages	251-281
Number of pages	31
Volume	1
ISBN (Electronic)	9781681081977
ISBN (Print)	9781681081984
DOIs	https://doi.org/10.1016/B978-1-68108-198-4.50011-4
State	Published - Jan 1 2015

Keywords

Adjacency matrix
Big data
Congenericity principle
Connectivity indices
Distance matrix
Diversity begets diversity principle
E-state indices
Envelope models
Graph theoretic matrices
Graph theory
Hierarchical quantitative structure-activity relationship (HiQSAR)
Information theoretic indices
Interrelated two-way clustering
Leave one out (LOO) method
Linear discriminant analysis
Molecular graphs
Mutagenicity
Naïve q
Partial least square (PLS)
Principal components analysis (PCA)
Principal components regression (PCR)
Proper cross validation
Property-activity relationship (PAR)
Quantum chemical descriptors
Ridge regression (RR)
Topochemical indices
Topological indices
Topostructural indices
True q
Valence connectivity indices
Weighted pseudograph

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Basak, S. C., & Majumdar, S. (2015). Current Landscape of Hierarchical QSAR Modeling and its Applications: Some Comments on the Importance of Mathematical Descriptors as well as Rigorous Statistical Methods of Model Building and Validation. In Advances in Mathematical Chemistry and Applications: Revised Edition (Vol. 1, pp. 251-281). Elsevier Inc.. https://doi.org/10.1016/B978-1-68108-198-4.50011-4

Current Landscape of Hierarchical QSAR Modeling and its Applications : Some Comments on the Importance of Mathematical Descriptors as well as Rigorous Statistical Methods of Model Building and Validation. / Basak, Subhash C.; Majumdar, Subhabrata.

Advances in Mathematical Chemistry and Applications: Revised Edition. Vol. 1 Elsevier Inc., 2015. p. 251-281.

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Basak, SC & Majumdar, S 2015, Current Landscape of Hierarchical QSAR Modeling and its Applications: Some Comments on the Importance of Mathematical Descriptors as well as Rigorous Statistical Methods of Model Building and Validation. in Advances in Mathematical Chemistry and Applications: Revised Edition. vol. 1, Elsevier Inc., pp. 251-281. https://doi.org/10.1016/B978-1-68108-198-4.50011-4

Basak SC, Majumdar S. Current Landscape of Hierarchical QSAR Modeling and its Applications: Some Comments on the Importance of Mathematical Descriptors as well as Rigorous Statistical Methods of Model Building and Validation. In Advances in Mathematical Chemistry and Applications: Revised Edition. Vol. 1. Elsevier Inc. 2015. p. 251-281 https://doi.org/10.1016/B978-1-68108-198-4.50011-4

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abstract = "Mathematical chemistry or more accurately discrete mathematical chemistry had a tremendous growth spurt in the second half of the twentieth century and the same trend is continuing in the twenty first century. This continual growth was fueled primarily by two major factors: 1) Novel applications of discrete mathematical concepts to chemical and biological systems, and 2) Availability of high speed computers and relevant software whereby hypothesis driven as well as discovery oriented research on large data sets could be carried out. This led to the development of not only a plethora of new concepts, but also to various useful applications. This chapter will discuss the major milestones in the development of hierarchical QSARs for the prediction of physical as well as biological properties of various classes of chemicals by the Basak group of researchers using mathematical descriptors and different statistical methods.",

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