New trends in qualitative analysis: Performance, optimization, and validation of multi-class and soft models

AL Pomerantsev, OY Rodionova - TrAC Trends in Analytical Chemistry, 2021 - Elsevier
This article considers current trends and challenges in qualitative analysis. The focus is not
on classification methods per se, but rather on their general features, such as the way the …

[图书][B] Understanding the basics of QSAR for applications in pharmaceutical sciences and risk assessment

K Roy, S Kar, RN Das - 2015 - books.google.com
Understanding the Basics of QSAR for Applications in Pharmaceutical Sciences and Risk
Assessment describes the historical evolution of quantitative structure-activity relationship …

Multivariate comparison of classification performance measures

D Ballabio, F Grisoni, R Todeschini - Chemometrics and Intelligent …, 2018 - Elsevier
The assessment of the classification performance can be based on class indices, such as
sensitivity, specificity and precision, which describe the classification results achieved on …

Probing the environmental toxicity of deep eutectic solvents and their components: An in silico modeling approach

AK Halder, MNDS Cordeiro - ACS Sustainable Chemistry & …, 2019 - ACS Publications
Because of the increasing demand of greener solvents, deep eutectic solvents (DES) have
just emerged as low-cost alternative solvents for a broad range of applications. However …

In silico prediction of chemical Ames mutagenicity

C Xu, F Cheng, L Chen, Z Du, W Li, G Liu… - Journal of chemical …, 2012 - ACS Publications
Mutagenicity is one of the most important end points of toxicity. Due to high cost and
laboriousness in experimental tests, it is necessary to develop robust in silico methods to …

Statistical methods in QSAR/QSPR

K Roy, S Kar, RN Das, K Roy, S Kar, RN Das - A Primer on QSAR/QSPR …, 2015 - Springer
QSAR/QSPR studies are aimed at developing correlation models using a response of
chemicals (activity/property) and chemical information data in a statistical approach. The …

QSAR of phytochemicals for the design of better drugs

S Kar, K Roy - Expert opinion on drug discovery, 2012 - Taylor & Francis
Introduction: Phytochemicals have been the single most prolific source of leads for the
development of new drug entities from the dawn of the drug discovery. They cover a wide …

In silico Prediction of Drug Induced Liver Toxicity Using Substructure Pattern Recognition Method

C Zhang, F Cheng, W Li, G Liu, PW Lee… - Molecular …, 2016 - Wiley Online Library
Drug‐induced liver injury (DILI) is a leading cause of acute liver failure in the US and less
severe liver injury worldwide. It is also one of the major reasons of drug withdrawal from the …

Prediction on the mutagenicity of nitroaromatic compounds using quantum chemistry descriptors based QSAR and machine learning derived classification methods

Y Hao, G Sun, T Fan, X Sun, Y Liu, N Zhang… - Ecotoxicology and …, 2019 - Elsevier
Nitroaromatic compounds (NACs) are an important type of environmental organic pollutants.
However, it is lack of sufficient information relating to their potential adverse effects on …

Evaluating the cytotoxicity of a large pool of metal oxide nanoparticles to Escherichia coli: Mechanistic understanding through In Vitro and In Silico studies

S Kar, K Pathakoti, PB Tchounwou, D Leszczynska… - Chemosphere, 2021 - Elsevier
The toxic effect of eight metal oxide nanoparticles (MONPs) on Escherichia coli was
experimentally evaluated following standard bioassay protocols. The obtained cytotoxicity …