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Items: 1 to 20 of 183

1.

Application of QSARs in identification of mutagenicity mechanisms of nitro and amino aromatic compounds against Salmonella typhimurium species.

Jillella GK, Khan K, Roy K.

Toxicol In Vitro. 2020 Jan 8;65:104768. doi: 10.1016/j.tiv.2020.104768. [Epub ahead of print]

PMID:
31926304
2.

Exploring 2D-QSAR for prediction of beta-secretase 1 (BACE1) inhibitory activity against Alzheimer's disease.

Kumar V, Ojha PK, Saha A, Roy K.

SAR QSAR Environ Res. 2020 Feb;31(2):87-133. doi: 10.1080/1062936X.2019.1695226.

PMID:
31865778
3.

Exploring QSAR modeling of toxicity of chemicals on earthworm.

Ghosh S, Ojha PK, Carnesecchi E, Lombardo A, Roy K, Benfenati E.

Ecotoxicol Environ Saf. 2020 Mar 1;190:110067. doi: 10.1016/j.ecoenv.2019.110067. Epub 2019 Dec 17.

PMID:
31855788
4.

First report on a classification-based QSAR model for chemical toxicity to earthworm.

Roy J, Kumar Ojha P, Carnesecchi E, Lombardo A, Roy K, Benfenati E.

J Hazard Mater. 2020 Mar 15;386:121660. doi: 10.1016/j.jhazmat.2019.121660. Epub 2019 Nov 10.

PMID:
31784141
5.

New Workflow for QSAR Model Development from Small Data Sets: Small Dataset Curator and Small Dataset Modeler. Integration of Data Curation, Exhaustive Double Cross-Validation, and a Set of Optimal Model Selection Techniques.

Ambure P, Gajewicz-Skretna A, Cordeiro MNDS, Roy K.

J Chem Inf Model. 2019 Oct 28;59(10):4070-4076. doi: 10.1021/acs.jcim.9b00476. Epub 2019 Sep 26.

PMID:
31525295
6.

Ecotoxicological QSAR modelling of organic chemicals against Pseudokirchneriella subcapitata using consensus predictions approach.

Khan K, Roy K.

SAR QSAR Environ Res. 2019 Sep 2:1-17. doi: 10.1080/1062936X.2019.1648315. [Epub ahead of print]

PMID:
31474156
7.

How Precise Are Our Quantitative Structure-Activity Relationship Derived Predictions for New Query Chemicals?

Roy K, Ambure P, Kar S.

ACS Omega. 2018 Sep 19;3(9):11392-11406. doi: 10.1021/acsomega.8b01647. eCollection 2018 Sep 30.

8.

QSPR Modeling of the Refractive Index for Diverse Polymers Using 2D Descriptors.

Khan PM, Rasulev B, Roy K.

ACS Omega. 2018 Oct 17;3(10):13374-13386. doi: 10.1021/acsomega.8b01834. eCollection 2018 Oct 31.

9.

Chemometric modeling to predict air half-life of persistent organic pollutants (POPs).

Khan PM, Baderna D, Lombardo A, Roy K, Benfenati E.

J Hazard Mater. 2020 Jan 15;382:121035. doi: 10.1016/j.jhazmat.2019.121035. Epub 2019 Aug 19.

PMID:
31450211
10.

Corrigendum to "QSAR modeling of Daphnia magna and fish toxicities of biocides using 2D descriptors" [Chemosphere 229 (2019) 8-17].

Khan K, Khan PM, Lavado G, Valsecchi C, Pasqualini J, Baderna D, Marzo M, Lombardo A, Roy K, Benfenati E.

Chemosphere. 2019 Dec;237:124397. doi: 10.1016/j.chemosphere.2019.124397. Epub 2019 Jul 20. No abstract available.

PMID:
31337507
11.

Ecotoxicological QSAR modeling of organic compounds against fish: Application of fragment based descriptors in feature analysis.

Khan K, Baderna D, Cappelli C, Toma C, Lombardo A, Roy K, Benfenati E.

Aquat Toxicol. 2019 Jul;212:162-174. doi: 10.1016/j.aquatox.2019.05.011. Epub 2019 May 17.

PMID:
31128417
12.

Consensus QSPR modelling for the prediction of cellular response and fibrinogen adsorption to the surface of polymeric biomaterials.

Khan PM, Roy K.

SAR QSAR Environ Res. 2019 May;30(5):363-382. doi: 10.1080/1062936X.2019.1607549.

PMID:
31112078
13.

QSAR modeling of Daphnia magna and fish toxicities of biocides using 2D descriptors.

Khan K, Khan PM, Lavado G, Valsecchi C, Pasqualini J, Baderna D, Marzo M, Lombardo A, Roy K, Benfenati E.

Chemosphere. 2019 Aug;229:8-17. doi: 10.1016/j.chemosphere.2019.04.204. Epub 2019 Apr 29. Erratum in: Chemosphere. 2019 Dec;237:124397.

PMID:
31063877
14.

Exploring QSPR modeling for adsorption of hazardous synthetic organic chemicals (SOCs) by SWCNTs.

Ghosh S, Ojha PK, Roy K.

Chemosphere. 2019 Aug;228:545-555. doi: 10.1016/j.chemosphere.2019.04.124. Epub 2019 Apr 23.

PMID:
31051358
15.

Target prioritization of novel substituted 5-aryl-2-oxo-/thioxo-2,3-dihydro-1H-benzo[6,7]chromeno[2,3-d]pyrimidine-4,6,11(5H)-triones as anticancer agents using in-silico approach.

Bhayye SS, Brahmachari G, Nayek N, Roy S, Roy K.

J Biomol Struct Dyn. 2019 Apr 10:1-10. doi: 10.1080/07391102.2019.1606735. [Epub ahead of print]

PMID:
30968736
16.

Risk assessment of heterogeneous TiO2-based engineered nanoparticles (NPs): a QSTR approach using simple periodic table based descriptors.

Roy J, Ojha PK, Roy K.

Nanotoxicology. 2019 Jun;13(5):701-716. doi: 10.1080/17435390.2019.1593543. Epub 2019 Apr 2.

PMID:
30938199
17.

Ecotoxicological QSAR modeling of endocrine disruptor chemicals.

Khan K, Roy K, Benfenati E.

J Hazard Mater. 2019 May 5;369:707-718. doi: 10.1016/j.jhazmat.2019.02.019. Epub 2019 Feb 21.

PMID:
30831523
18.

Chemometric modeling of Daphnia magna toxicity of agrochemicals.

Khan PM, Roy K, Benfenati E.

Chemosphere. 2019 Jun;224:470-479. doi: 10.1016/j.chemosphere.2019.02.147. Epub 2019 Feb 25.

PMID:
30831498
19.

Computational Approaches as Rational Decision Support Systems for Discovering Next-Generation Antitubercular Agents: Mini-Review.

Aher RB, Roy K.

Curr Comput Aided Drug Des. 2019;15(5):369-383. doi: 10.2174/1573409915666190130153214.

PMID:
30706823
20.

Patch-based system for Classification of Breast Histology images using deep learning.

Roy K, Banik D, Bhattacharjee D, Nasipuri M.

Comput Med Imaging Graph. 2019 Jan;71:90-103. doi: 10.1016/j.compmedimag.2018.11.003. Epub 2018 Dec 1.

PMID:
30594745

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