BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

131 related articles for article (PubMed ID: 32526407)

  • 1. Is intraspecies QSTR model answer to toxicity data gap filling: Ecotoxicity modeling of chemicals to avian species.
    Kar S; Leszczynski J
    Sci Total Environ; 2020 Oct; 738():139858. PubMed ID: 32526407
    [TBL] [Abstract][Full Text] [Related]  

  • 2. First report on ecotoxicological QSTR and i-QSTR modeling for the prediction of acute ecotoxicity of diverse organic chemicals against three protozoan species.
    Kumar A; Kumar V; Podder T; Ojha PK
    Chemosphere; 2023 Sep; 335():139066. PubMed ID: 37257655
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Ecotoxicological Modeling, Ranking and Prioritization of Pharmaceuticals Using QSTR and i-QSTTR Approaches: Application of 2D and Fragment Based Descriptors.
    Khan K; Kar S; Sanderson H; Roy K; Leszczynski J
    Mol Inform; 2019 Aug; 38(8-9):e1800078. PubMed ID: 30474352
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Ecotoxicological QSTR and QSTTR Modeling for the Prediction of Acute Oral Toxicity of Pesticides against Multiple Avian Species.
    Mukherjee RK; Kumar V; Roy K
    Environ Sci Technol; 2022 Jan; 56(1):335-348. PubMed ID: 34905924
    [TBL] [Abstract][Full Text] [Related]  

  • 5. First report on chemometric modeling of tilapia fish aquatic toxicity to organic chemicals: Toxicity data gap filling.
    Yang S; Kar S
    Sci Total Environ; 2024 Jan; 907():167991. PubMed ID: 37898216
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Computational tool for risk assessment of nanomaterials: novel QSTR-perturbation model for simultaneous prediction of ecotoxicity and cytotoxicity of uncoated and coated nanoparticles under multiple experimental conditions.
    Kleandrova VV; Luan F; González-Díaz H; Ruso JM; Speck-Planche A; Cordeiro MN
    Environ Sci Technol; 2014 Dec; 48(24):14686-94. PubMed ID: 25384130
    [TBL] [Abstract][Full Text] [Related]  

  • 7. QSTR modeling for qualitative and quantitative toxicity predictions of diverse chemical pesticides in honey bee for regulatory purposes.
    Singh KP; Gupta S; Basant N; Mohan D
    Chem Res Toxicol; 2014 Sep; 27(9):1504-15. PubMed ID: 25167463
    [TBL] [Abstract][Full Text] [Related]  

  • 8. In silico prediction of toxicity of non-congeneric industrial chemicals using ensemble learning based modeling approaches.
    Singh KP; Gupta S
    Toxicol Appl Pharmacol; 2014 Mar; 275(3):198-212. PubMed ID: 24463095
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Chemometric modeling of aquatic toxicity of contaminants of emerging concern (CECs) in Dugesia japonica and its interspecies correlation with daphnia and fish: QSTR and QSTTR approaches.
    Hossain KA; Roy K
    Ecotoxicol Environ Saf; 2018 Dec; 166():92-101. PubMed ID: 30253287
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Interspecies quantitative structure-toxicity-toxicity (QSTTR) relationship modeling of ionic liquids. Toxicity of ionic liquids to V. fischeri, D. magna and S. vacuolatus.
    Das RN; Roy K; Popelier PL
    Ecotoxicol Environ Saf; 2015 Dec; 122():497-520. PubMed ID: 26414597
    [TBL] [Abstract][Full Text] [Related]  

  • 11. On the aquatic toxicity of substituted phenols to Chlorella vulgaris: QSTR with an extended novel data set and interspecies models.
    Tugcu G; Ertürk MD; Saçan MT
    J Hazard Mater; 2017 Oct; 339():122-130. PubMed ID: 28641232
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Predictive ecotoxicity of MoA 1 of organic chemicals using in silico approaches.
    de Morais E Silva L; Alves MF; Scotti L; Lopes WS; Scotti MT
    Ecotoxicol Environ Saf; 2018 May; 153():151-159. PubMed ID: 29427976
    [TBL] [Abstract][Full Text] [Related]  

  • 13. In silico prediction of toxicity of phenols to Tetrahymena pyriformis by using genetic algorithm and decision tree-based modeling approach.
    Abbasitabar F; Zare-Shahabadi V
    Chemosphere; 2017 Apr; 172():249-259. PubMed ID: 28081509
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Toxicity of contaminants of emerging concern to Dugesia japonica: QSTR modeling and toxicity relationship with Daphnia magna.
    Önlü S; Saçan MT
    J Hazard Mater; 2018 Jun; 351():20-28. PubMed ID: 29506002
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Predicting aquatic toxicities of chemical pesticides in multiple test species using nonlinear QSTR modeling approaches.
    Basant N; Gupta S; Singh KP
    Chemosphere; 2015 Nov; 139():246-55. PubMed ID: 26142614
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Predictive classification-based QSTR models for toxicity study of diverse pesticides on multiple avian species.
    Banjare P; Singh J; Roy PP
    Environ Sci Pollut Res Int; 2021 Apr; 28(14):17992-18003. PubMed ID: 33410022
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Predicting the ecotoxicity of endocrine disruptive chemicals: Multitasking in silico approaches towards global models.
    Halder AK; Moura AS; Cordeiro MNDS
    Sci Total Environ; 2023 Sep; 889():164337. PubMed ID: 37211130
    [TBL] [Abstract][Full Text] [Related]  

  • 18. MOA-based linear and nonlinear QSAR models for predicting the toxicity of organic chemicals to Vibrio fischeri.
    Zhang S; Wang N; Su L; Xu X; Li C; Qin W; Zhao Y
    Environ Sci Pollut Res Int; 2020 Mar; 27(9):9114-9125. PubMed ID: 31916172
    [TBL] [Abstract][Full Text] [Related]  

  • 19. An in silico algal toxicity model with a wide applicability potential for industrial chemicals and pharmaceuticals.
    Önlü S; Saçan MT
    Environ Toxicol Chem; 2017 Apr; 36(4):1012-1019. PubMed ID: 27617782
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Toxicity prediction of 1,2,4-triazoles compounds by QSTR and interspecies QSTTR models.
    Liu Z; Dang K; Gao J; Fan P; Li C; Wang H; Li H; Deng X; Gao Y; Qian A
    Ecotoxicol Environ Saf; 2022 Sep; 242():113839. PubMed ID: 35816839
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.