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Journal Abstract Search

264 related items for PubMed ID: 33987446

  • 1. An Ensemble Learning-Based Method for Inferring Drug-Target Interactions Combining Protein Sequences and Drug Fingerprints.
    Zhao ZY, Huang WZ, Zhan XK, Pan J, Huang YA, Zhang SW, Yu CQ.
    Biomed Res Int; 2021; 2021():9933873. PubMed ID: 33987446
    [Abstract] [Full Text] [Related]

  • 2. Improved prediction of drug-target interactions based on ensemble learning with fuzzy local ternary pattern.
    Zhao ZY, Huang WZ, Zhan XK, Huang YA, Zhang SW, Yu CQ.
    Front Biosci (Landmark Ed); 2021 Jul 30; 26(7):222-234. PubMed ID: 34340269
    [Abstract] [Full Text] [Related]

  • 3. Ensemble Learning Prediction of Drug-Target Interactions Using GIST Descriptor Extracted from PSSM-Based Evolutionary Information.
    Zhan X, You Z, Yu C, Li L, Pan J.
    Biomed Res Int; 2020 Jul 30; 2020():4516250. PubMed ID: 32908888
    [Abstract] [Full Text] [Related]

  • 4. Drug-Target Interaction Prediction Based on Drug Fingerprint Information and Protein Sequence.
    Li Y, Huang YA, You ZH, Li LP, Wang Z.
    Molecules; 2019 Aug 19; 24(16):. PubMed ID: 31430892
    [Abstract] [Full Text] [Related]

  • 5. Incorporating chemical sub-structures and protein evolutionary information for inferring drug-target interactions.
    Wang L, You ZH, Li LP, Yan X, Zhang W.
    Sci Rep; 2020 Apr 20; 10(1):6641. PubMed ID: 32313024
    [Abstract] [Full Text] [Related]

  • 6. An efficient computational method for predicting drug-target interactions using weighted extreme learning machine and speed up robot features.
    An JY, Meng FR, Yan ZJ.
    BioData Min; 2021 Jan 20; 14(1):3. PubMed ID: 33472664
    [Abstract] [Full Text] [Related]

  • 7. Prediction of Drug-Target Interactions by Combining Dual-Tree Complex Wavelet Transform with Ensemble Learning Method.
    Pan J, Li LP, You ZH, Yu CQ, Ren ZH, Chen Y.
    Molecules; 2021 Sep 03; 26(17):. PubMed ID: 34500792
    [Abstract] [Full Text] [Related]

  • 8. Identification of potential drug-targets by combining evolutionary information extracted from frequency profiles and molecular topological structures.
    Wang L, You ZH, Li LP, Yan X, Zhang W, Song KJ, Song CD.
    Chem Biol Drug Des; 2020 Aug 03; 96(2):758-767. PubMed ID: 31393672
    [Abstract] [Full Text] [Related]

  • 9. In silico prediction of drug-target interaction networks based on drug chemical structure and protein sequences.
    Li Z, Han P, You ZH, Li X, Zhang Y, Yu H, Nie R, Chen X.
    Sci Rep; 2017 Sep 11; 7(1):11174. PubMed ID: 28894115
    [Abstract] [Full Text] [Related]

  • 10. Prediction of Drug-Target Interaction Networks from the Integration of Protein Sequences and Drug Chemical Structures.
    Meng FR, You ZH, Chen X, Zhou Y, An JY.
    Molecules; 2017 Jul 05; 22(7):. PubMed ID: 28678206
    [Abstract] [Full Text] [Related]

  • 11. DeepStack-DTIs: Predicting Drug-Target Interactions Using LightGBM Feature Selection and Deep-Stacked Ensemble Classifier.
    Zhang Y, Jiang Z, Chen C, Wei Q, Gu H, Yu B.
    Interdiscip Sci; 2022 Jun 05; 14(2):311-330. PubMed ID: 34731411
    [Abstract] [Full Text] [Related]

  • 12. Accurate prediction of protein-protein interactions by integrating potential evolutionary information embedded in PSSM profile and discriminative vector machine classifier.
    Li ZW, You ZH, Chen X, Li LP, Huang DS, Yan GY, Nie R, Huang YA.
    Oncotarget; 2017 Apr 04; 8(14):23638-23649. PubMed ID: 28423569
    [Abstract] [Full Text] [Related]

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  • 14. Predicting drug-target interactions using Lasso with random forest based on evolutionary information and chemical structure.
    Shi H, Liu S, Chen J, Li X, Ma Q, Yu B.
    Genomics; 2019 Dec 04; 111(6):1839-1852. PubMed ID: 30550813
    [Abstract] [Full Text] [Related]

  • 15. RFDT: A Rotation Forest-based Predictor for Predicting Drug-Target Interactions Using Drug Structure and Protein Sequence Information.
    Wang L, You ZH, Chen X, Yan X, Liu G, Zhang W.
    Curr Protein Pept Sci; 2018 Dec 04; 19(5):445-454. PubMed ID: 27842479
    [Abstract] [Full Text] [Related]

  • 16. PCVMZM: Using the Probabilistic Classification Vector Machines Model Combined with a Zernike Moments Descriptor to Predict Protein-Protein Interactions from Protein Sequences.
    Wang Y, You Z, Li X, Chen X, Jiang T, Zhang J.
    Int J Mol Sci; 2017 May 11; 18(5):. PubMed ID: 28492483
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  • 18. Ens-PPI: A Novel Ensemble Classifier for Predicting the Interactions of Proteins Using Autocovariance Transformation from PSSM.
    Gao ZG, Wang L, Xia SX, You ZH, Yan X, Zhou Y.
    Biomed Res Int; 2016 May 11; 2016():4563524. PubMed ID: 27437399
    [Abstract] [Full Text] [Related]

  • 19. An Ensemble Classifier to Predict Protein-Protein Interactions by Combining PSSM-based Evolutionary Information with Local Binary Pattern Model.
    Li Y, Li LP, Wang L, Yu CQ, Wang Z, You ZH.
    Int J Mol Sci; 2019 Jul 17; 20(14):. PubMed ID: 31319578
    [Abstract] [Full Text] [Related]

  • 20. PreDTIs: prediction of drug-target interactions based on multiple feature information using gradient boosting framework with data balancing and feature selection techniques.
    Mahmud SMH, Chen W, Liu Y, Awal MA, Ahmed K, Rahman MH, Moni MA.
    Brief Bioinform; 2021 Sep 02; 22(5):. PubMed ID: 33709119
    [Abstract] [Full Text] [Related]

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