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 *

110 related articles for article (PubMed ID: 35868454)

  • 1. deepGraphh: AI-driven web service for graph-based quantitative structure-activity relationship analysis.
    Gautam V; Gupta R; Gupta D; Ruhela A; Mittal A; Mohanty SK; Arora S; Gupta R; Saini C; Sengupta D; Murugan NA; Ahuja G
    Brief Bioinform; 2022 Sep; 23(5):. PubMed ID: 35868454
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Hyperbolic relational graph convolution networks plus: a simple but highly efficient QSAR-modeling method.
    Wu Z; Jiang D; Hsieh CY; Chen G; Liao B; Cao D; Hou T
    Brief Bioinform; 2021 Sep; 22(5):. PubMed ID: 33866354
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Intelligently Applying Artificial Intelligence in Chemoinformatics.
    Sharma S; Sharma D
    Curr Top Med Chem; 2018; 18(20):1804-1826. PubMed ID: 30465503
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Chemical graphs, molecular matrices and topological indices in chemoinformatics and quantitative structure-activity relationships.
    Ivanciuc O
    Curr Comput Aided Drug Des; 2013 Jun; 9(2):153-63. PubMed ID: 23701000
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Artificial Intelligence-Based Toxicity Prediction of Environmental Chemicals: Future Directions for Chemical Management Applications.
    Jeong J; Choi J
    Environ Sci Technol; 2022 Jun; 56(12):7532-7543. PubMed ID: 35666838
    [TBL] [Abstract][Full Text] [Related]  

  • 6. 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]  

  • 7. Comprehensive evaluation of deep and graph learning on drug-drug interactions prediction.
    Lin X; Dai L; Zhou Y; Yu ZG; Zhang W; Shi JY; Cao DS; Zeng L; Chen H; Song B; Yu PS; Zeng X
    Brief Bioinform; 2023 Jul; 24(4):. PubMed ID: 37401373
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Bio-AIMS Collection of Chemoinformatics Web Tools based on Molecular Graph Information and Artificial Intelligence Models.
    Munteanu CR; Gonzalez-Diaz H; Garcia R; Loza M; Pazos A
    Comb Chem High Throughput Screen; 2015; 18(8):735-50. PubMed ID: 26234511
    [TBL] [Abstract][Full Text] [Related]  

  • 9. QSAR modeling of the blood-brain barrier permeability for diverse organic compounds.
    Zhang L; Zhu H; Oprea TI; Golbraikh A; Tropsha A
    Pharm Res; 2008 Aug; 25(8):1902-14. PubMed ID: 18553217
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Artificial intelligence in drug discovery: recent advances and future perspectives.
    Jiménez-Luna J; Grisoni F; Weskamp N; Schneider G
    Expert Opin Drug Discov; 2021 Sep; 16(9):949-959. PubMed ID: 33779453
    [No Abstract]   [Full Text] [Related]  

  • 11. A Recurrent Neural Network model to predict blood-brain barrier permeability.
    Alsenan S; Al-Turaiki I; Hafez A
    Comput Biol Chem; 2020 Dec; 89():107377. PubMed ID: 33010784
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Spatio-temporal directed acyclic graph learning with attention mechanisms on brain functional time series and connectivity.
    Huang SG; Xia J; Xu L; Qiu A
    Med Image Anal; 2022 Apr; 77():102370. PubMed ID: 35144197
    [TBL] [Abstract][Full Text] [Related]  

  • 13. AI-enhanced chemical paradigm: From molecular graphs to accurate prediction and mechanism.
    Huang Z; Yu J; He W; Yu J; Deng S; Yang C; Zhu W; Shao X
    J Hazard Mater; 2024 Mar; 465():133355. PubMed ID: 38198864
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Graph Signal Processing Approach to QSAR/QSPR Model Learning of Compounds.
    Song X; Chai L; Zhang J
    IEEE Trans Pattern Anal Mach Intell; 2022 Apr; 44(4):1963-1973. PubMed ID: 33085613
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Prediction on the mutagenicity of nitroaromatic compounds using quantum chemistry descriptors based QSAR and machine learning derived classification methods.
    Hao Y; Sun G; Fan T; Sun X; Liu Y; Zhang N; Zhao L; Zhong R; Peng Y
    Ecotoxicol Environ Saf; 2019 Dec; 186():109822. PubMed ID: 31634658
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Developing Enhanced Blood-Brain Barrier Permeability Models: Integrating External Bio-Assay Data in QSAR Modeling.
    Wang W; Kim MT; Sedykh A; Zhu H
    Pharm Res; 2015 Sep; 32(9):3055-65. PubMed ID: 25862462
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Alvascience: A New Software Suite for the QSAR Workflow Applied to the Blood-Brain Barrier Permeability.
    Mauri A; Bertola M
    Int J Mol Sci; 2022 Oct; 23(21):. PubMed ID: 36361669
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Applicability Domain for Trustable Predictions.
    Yang S; Kar S
    Methods Mol Biol; 2025; 2834():131-149. PubMed ID: 39312163
    [TBL] [Abstract][Full Text] [Related]  

  • 19. A comparative QSAR study using CoMFA, HQSAR, and FRED/SKEYS paradigms for estrogen receptor binding affinities of structurally diverse compounds.
    Waller CL
    J Chem Inf Comput Sci; 2004; 44(2):758-65. PubMed ID: 15032558
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Predicting scalar coupling constants by graph angle-attention neural network.
    Fang J; Hu L; Dong J; Li H; Wang H; Zhao H; Zhang Y; Liu M
    Sci Rep; 2021 Sep; 11(1):18686. PubMed ID: 34548513
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 6.