BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

185 related articles for article (PubMed ID: 37762462)

  • 1. Cheminformatics and Machine Learning Approaches to Assess Aquatic Toxicity Profiles of Fullerene Derivatives.
    Fjodorova N; Novič M; Venko K; Rasulev B; Türker Saçan M; Tugcu G; Sağ Erdem S; Toropova AP; Toropov AA
    Int J Mol Sci; 2023 Sep; 24(18):. PubMed ID: 37762462
    [TBL] [Abstract][Full Text] [Related]  

  • 2. How fullerene derivatives (FDs) act on therapeutically important targets associated with diabetic diseases.
    Fjodorova N; Novič M; Venko K; Drgan V; Rasulev B; Türker Saçan M; Sağ Erdem S; Tugcu G; Toropova AP; Toropov AA
    Comput Struct Biotechnol J; 2022; 20():913-924. PubMed ID: 35242284
    [TBL] [Abstract][Full Text] [Related]  

  • 3. A Comprehensive Cheminformatics Analysis of Structural Features Affecting the Binding Activity of Fullerene Derivatives.
    Fjodorova N; Novič M; Venko K; Rasulev B
    Nanomaterials (Basel); 2020 Jan; 10(1):. PubMed ID: 31906497
    [TBL] [Abstract][Full Text] [Related]  

  • 4. The Influence of Structural Patterns on Acute Aquatic Toxicity of Organic Compounds.
    Tinkov O; Polishchuk P; Matveieva M; Grigorev V; Grigoreva L; Porozov Y
    Mol Inform; 2021 Sep; 40(9):e2000209. PubMed ID: 33029954
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Modeling and insights into the structural basis of chemical acute aquatic toxicity.
    Zhang R; Guo H; Hua Y; Cui X; Shi Y; Li X
    Ecotoxicol Environ Saf; 2022 Sep; 242():113940. PubMed ID: 35999760
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Developing random forest based QSAR models for predicting the mixture toxicity of TiO
    Trinh TX; Seo M; Yoon TH; Kim J
    NanoImpact; 2022 Jan; 25():100383. PubMed ID: 35559889
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Hazard of pharmaceuticals for aquatic environment: Prioritization by structural approaches and prediction of ecotoxicity.
    Sangion A; Gramatica P
    Environ Int; 2016 Oct; 95():131-43. PubMed ID: 27568576
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Insights into pesticide toxicity against aquatic organism: QSTR models on Daphnia Magna.
    He L; Xiao K; Zhou C; Li G; Yang H; Li Z; Cheng J
    Ecotoxicol Environ Saf; 2019 May; 173():285-292. PubMed ID: 30776561
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Evaluation of modes of action of pesticides to Daphnia magna based on QSAR, excess toxicity and critical body residues.
    Wang J; Yang Y; Huang Y; Zhang X; Huang Y; Qin WC; Wen Y; Zhao YH
    Ecotoxicol Environ Saf; 2020 Oct; 203():111046. PubMed ID: 32888614
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Identification and regulation of ecotoxicity of polychlorinated naphthalenes to aquatic food Chain (green algae-Daphnia magna-fish).
    Gu W; Li X; Du M; Ren Z; Li Q; Li Y
    Aquat Toxicol; 2021 Apr; 233():105774. PubMed ID: 33610856
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Machine Learning Models for Identification and Prediction of Toxic Organic Compounds Using
    Choi TJ; An HE; Kim CB
    Life (Basel); 2022 Sep; 12(9):. PubMed ID: 36143479
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Using Machine Learning to Predict Adverse Effects of Metallic Nanomaterials to Various Aquatic Organisms.
    Zhou Y; Wang Y; Peijnenburg W; Vijver MG; Balraadjsing S; Fan W
    Environ Sci Technol; 2023 Nov; 57(46):17786-17795. PubMed ID: 36730792
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Machine learning models for predicting the activity of AChE and BACE1 dual inhibitors for the treatment of Alzheimer's disease.
    Dhamodharan G; Mohan CG
    Mol Divers; 2022 Jun; 26(3):1501-1517. PubMed ID: 34327619
    [TBL] [Abstract][Full Text] [Related]  

  • 14. An Update Report on the Biosafety and Potential Toxicity of Fullerene-Based Nanomaterials toward Aquatic Animals.
    Malhotra N; Audira G; Castillo AL; Siregar P; Ruallo JMS; Roldan MJ; Chen JR; Lee JS; Ger TR; Hsiao CD
    Oxid Med Cell Longev; 2021; 2021():7995223. PubMed ID: 34336114
    [TBL] [Abstract][Full Text] [Related]  

  • 15. A zeta potential value determines the aggregate's size of penta-substituted [60]fullerene derivatives in aqueous suspension whereas positive charge is required for toxicity against bacterial cells.
    Deryabin DG; Efremova LV; Vasilchenko AS; Saidakova EV; Sizova EA; Troshin PA; Zhilenkov AV; Khakina EA
    J Nanobiotechnology; 2015 Aug; 13():50. PubMed ID: 26253116
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Synergy between machine learning and natural products cheminformatics: Application to the lead discovery of anthraquinone derivatives.
    Moshawih S; Goh HP; Kifli N; Idris AC; Yassin H; Kotra V; Goh KW; Liew KB; Ming LC
    Chem Biol Drug Des; 2022 Aug; 100(2):185-217. PubMed ID: 35490393
    [TBL] [Abstract][Full Text] [Related]  

  • 17. New Insights on the Influence of Organic Co-Contaminants on the Aquatic Toxicology of Carbon Nanomaterials.
    Sanchís J; Olmos M; Vincent P; Farré M; Barceló D
    Environ Sci Technol; 2016 Jan; 50(2):961-9. PubMed ID: 26694946
    [TBL] [Abstract][Full Text] [Related]  

  • 18. QSAR models for biocides: The example of the prediction of
    Marzo M; Lavado GJ; Como F; Toropova AP; Toropov AA; Baderna D; Cappelli C; Lombardo A; Toma C; Blázquez M; Benfenati E
    SAR QSAR Environ Res; 2020 Mar; 31(3):227-243. PubMed ID: 31941347
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Response of biochemical biomarkers in the aquatic crustacean Daphnia magna exposed to silver nanoparticles.
    Ulm L; Krivohlavek A; Jurašin D; Ljubojević M; Šinko G; Crnković T; Žuntar I; Šikić S; Vinković Vrček I
    Environ Sci Pollut Res Int; 2015 Dec; 22(24):19990-9. PubMed ID: 26296504
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Behavioural and chronic toxicity of fullerene to Daphnia magna: Mechanisms revealed by transcriptomic analysis.
    Wang P; Huang B; Chen Z; Lv X; Qian W; Zhu X; Li B; Wang Z; Cai Z
    Environ Pollut; 2019 Dec; 255(Pt 1):113181. PubMed ID: 31522006
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.