These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

198 related articles for article (PubMed ID: 28031013)

  • 1. Development of a Web-Enabled SVR-Based Machine Learning Platform and its Application on Modeling Transgene Expression Activity of Aminoglycoside-Derived Polycations.
    Zhen Z; Potta T; Lanzillo NA; Rege K; Breneman CM
    Comb Chem High Throughput Screen; 2017; 20(1):41-55. PubMed ID: 28031013
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Discovery of antibiotics-derived polymers for gene delivery using combinatorial synthesis and cheminformatics modeling.
    Potta T; Zhen Z; Grandhi TS; Christensen MD; Ramos J; Breneman CM; Rege K
    Biomaterials; 2014 Feb; 35(6):1977-88. PubMed ID: 24331709
    [TBL] [Abstract][Full Text] [Related]  

  • 3. QSPR modelling for investigation of different properties of aminoglycoside-derived polymers using 2D descriptors.
    Khan PM; Roy K
    SAR QSAR Environ Res; 2021 Jul; 32(7):595-614. PubMed ID: 34148451
    [TBL] [Abstract][Full Text] [Related]  

  • 4. ChemSuite: A package for chemoinformatics calculations and machine learning.
    Tangadpalliwar SR; Vishwakarma S; Nimbalkar R; Garg P
    Chem Biol Drug Des; 2019 May; 93(5):960-964. PubMed ID: 30637953
    [TBL] [Abstract][Full Text] [Related]  

  • 5. AutoWeka: toward an automated data mining software for QSAR and QSPR studies.
    Nantasenamat C; Worachartcheewan A; Jamsak S; Preeyanon L; Shoombuatong W; Simeon S; Mandi P; Isarankura-Na-Ayudhya C; Prachayasittikul V
    Methods Mol Biol; 2015; 1260():119-47. PubMed ID: 25502379
    [TBL] [Abstract][Full Text] [Related]  

  • 6. QSAR study on 5-lipoxygenase inhibitors based on support vector machine.
    Niu B; Su Q; Yuan X; Lu W; Ding J
    Med Chem; 2012 Nov; 8(6):1108-16. PubMed ID: 22779798
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Regression methods for developing QSAR and QSPR models to predict compounds of specific pharmacodynamic, pharmacokinetic and toxicological properties.
    Yap CW; Li H; Ji ZL; Chen YZ
    Mini Rev Med Chem; 2007 Nov; 7(11):1097-107. PubMed ID: 18045213
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Online monitoring and control of particle size in the grinding process using least square support vector regression and resilient back propagation neural network.
    Pani AK; Mohanta HK
    ISA Trans; 2015 May; 56():206-21. PubMed ID: 25528293
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Evaluation of mutual information, genetic algorithm and SVR for feature selection in QSAR regression.
    Fang J; Tai D
    Curr Drug Discov Technol; 2011 Jun; 8(2):107-11. PubMed ID: 21513488
    [TBL] [Abstract][Full Text] [Related]  

  • 10. In Silico Study of In Vitro GPCR Assays by QSAR Modeling.
    Mansouri K; Judson RS
    Methods Mol Biol; 2016; 1425():361-81. PubMed ID: 27311474
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Non-linear modeling and chemical interpretation with aid of support vector machine and regression.
    Hasegawa K; Funatsu K
    Curr Comput Aided Drug Des; 2010 Mar; 6(1):24-36. PubMed ID: 20370693
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Ranking chemical structures for drug discovery: a new machine learning approach.
    Agarwal S; Dugar D; Sengupta S
    J Chem Inf Model; 2010 May; 50(5):716-31. PubMed ID: 20387860
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Incremental learning for ν-Support Vector Regression.
    Gu B; Sheng VS; Wang Z; Ho D; Osman S; Li S
    Neural Netw; 2015 Jul; 67():140-50. PubMed ID: 25933108
    [TBL] [Abstract][Full Text] [Related]  

  • 14. ChemModLab: a web-based cheminformatics modeling laboratory.
    Hughes-Oliver JM; Brooks AD; Welch WJ; Khaledi MG; Hawkins D; Young SS; Patil K; Howell GW; Ng RT; Chu MT
    In Silico Biol; 2011-2012; 11(1-2):61-81. PubMed ID: 22475752
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Prediction of the aquatic toxicity of aromatic compounds to tetrahymena pyriformis through support vector regression.
    Su Q; Lu W; Du D; Chen F; Niu B; Chou KC
    Oncotarget; 2017 Jul; 8(30):49359-49369. PubMed ID: 28467816
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Exploring Alternative Strategies for the Identification of Potent Compounds Using Support Vector Machine and Regression Modeling.
    Miyao T; Funatsu K; Bajorath J
    J Chem Inf Model; 2019 Mar; 59(3):983-992. PubMed ID: 30547580
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Developing a dengue forecast model using machine learning: A case study in China.
    Guo P; Liu T; Zhang Q; Wang L; Xiao J; Zhang Q; Luo G; Li Z; He J; Zhang Y; Ma W
    PLoS Negl Trop Dis; 2017 Oct; 11(10):e0005973. PubMed ID: 29036169
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Recent Advances in Machine-Learning-Based Chemoinformatics: A Comprehensive Review.
    Niazi SK; Mariam Z
    Int J Mol Sci; 2023 Jul; 24(14):. PubMed ID: 37511247
    [TBL] [Abstract][Full Text] [Related]  

  • 19. An Analysis of QSAR Research Based on Machine Learning Concepts.
    Keyvanpour MR; Shirzad MB
    Curr Drug Discov Technol; 2021; 18(1):17-30. PubMed ID: 32178612
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Support vector machine-based quantitative structure-activity relationship study of cholesteryl ester transfer protein inhibitors.
    Riahi S; Pourbasheer E; Ganjali MR; Norouzi P
    Chem Biol Drug Des; 2009 May; 73(5):558-71. PubMed ID: 19323654
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.