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.


Pubmed for Handhelds

PUBMED FOR HANDHELDS

Journal Abstract Search

296 related items for PubMed ID: 28088356

  • 1. Advancing the prediction accuracy of protein-protein interactions by utilizing evolutionary information from position-specific scoring matrix and ensemble classifier.
    Wang L, You ZH, Xia SX, Liu F, Chen X, Yan X, Zhou Y.
    J Theor Biol; 2017 Apr 07; 418():105-110. PubMed ID: 28088356
    [Abstract] [Full Text] [Related]

  • 2. RVMAB: Using the Relevance Vector Machine Model Combined with Average Blocks to Predict the Interactions of Proteins from Protein Sequences.
    An JY, You ZH, Meng FR, Xu SJ, Wang Y.
    Int J Mol Sci; 2016 May 18; 17(5):. PubMed ID: 27213337
    [Abstract] [Full Text] [Related]

  • 3. Improving protein-protein interactions prediction accuracy using protein evolutionary information and relevance vector machine model.
    An JY, Meng FR, You ZH, Chen X, Yan GY, Hu JP.
    Protein Sci; 2016 Oct 18; 25(10):1825-33. PubMed ID: 27452983
    [Abstract] [Full Text] [Related]

  • 4. 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]

  • 5. An ensemble approach for large-scale identification of protein- protein interactions using the alignments of multiple sequences.
    Wang L, You ZH, Chen X, Li JQ, Yan X, Zhang W, Huang YA.
    Oncotarget; 2017 Jan 17; 8(3):5149-5159. PubMed ID: 28029645
    [Abstract] [Full Text] [Related]

  • 6. Predicting Protein-Protein Interactions via Random Ferns with Evolutionary Matrix Representation.
    Li Y, Wang Z, You ZH, Li LP, Hu X.
    Comput Math Methods Med; 2022 Jan 17; 2022():7191684. PubMed ID: 35242211
    [Abstract] [Full Text] [Related]

  • 7. 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 Jan 17; 2016():4563524. PubMed ID: 27437399
    [Abstract] [Full Text] [Related]

  • 8. 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
    [Abstract] [Full Text] [Related]

  • 9. Detection of Interactions between Proteins through Rotation Forest and Local Phase Quantization Descriptors.
    Wong L, You ZH, Ming Z, Li J, Chen X, Huang YA.
    Int J Mol Sci; 2015 Dec 24; 17(1):. PubMed ID: 26712745
    [Abstract] [Full Text] [Related]

  • 10.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 11. Detection of Interactions between Proteins by Using Legendre Moments Descriptor to Extract Discriminatory Information Embedded in PSSM.
    Wang YB, You ZH, Li LP, Huang YA, Yi HC.
    Molecules; 2017 Aug 18; 22(8):. PubMed ID: 28820478
    [Abstract] [Full Text] [Related]

  • 12. 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]

  • 13. Predicting Protein-Protein Interactions from Matrix-Based Protein Sequence Using Convolution Neural Network and Feature-Selective Rotation Forest.
    Wang L, Wang HF, Liu SR, Yan X, Song KJ.
    Sci Rep; 2019 Jul 08; 9(1):9848. PubMed ID: 31285519
    [Abstract] [Full Text] [Related]

  • 14.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 15. Highly accurate prediction of protein self-interactions by incorporating the average block and PSSM information into the general PseAAC.
    Zhai JX, Cao TJ, An JY, Bian YT.
    J Theor Biol; 2017 Nov 07; 432():80-86. PubMed ID: 28802824
    [Abstract] [Full Text] [Related]

  • 16.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 17.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 18.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 19. 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 Nov 07; 19(5):445-454. PubMed ID: 27842479
    [Abstract] [Full Text] [Related]

  • 20.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

    Page: [Next] [New Search]
    of 15.