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Journal Abstract Search

199 related items for PubMed ID: 31874626

  • 1. Using discriminative vector machine model with 2DPCA to predict interactions among proteins.
    Li Z, Nie R, You Z, Cao C, Li J.
    BMC Bioinformatics; 2019 Dec 24; 20(Suppl 25):694. PubMed ID: 31874626
    [Abstract] [Full Text] [Related]

  • 2. 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]

  • 3. 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]

  • 4. 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]

  • 5. 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 11; 25(10):1825-33. PubMed ID: 27452983
    [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 Oct 11; 2022():7191684. PubMed ID: 35242211
    [Abstract] [Full Text] [Related]

  • 7. 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]

  • 8. Prediction of protein-protein interactions from amino acid sequences with ensemble extreme learning machines and principal component analysis.
    You ZH, Lei YK, Zhu L, Xia J, Wang B.
    BMC Bioinformatics; 2013 Aug 18; 14 Suppl 8(Suppl 8):S10. PubMed ID: 23815620
    [Abstract] [Full Text] [Related]

  • 9. 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]

  • 10. Highly Accurate Prediction of Protein-Protein Interactions via Incorporating Evolutionary Information and Physicochemical Characteristics.
    Li ZW, You ZH, Chen X, Gui J, Nie R.
    Int J Mol Sci; 2016 Aug 25; 17(9):. PubMed ID: 27571061
    [Abstract] [Full Text] [Related]

  • 11. Improved protein-protein interactions prediction via weighted sparse representation model combining continuous wavelet descriptor and PseAA composition.
    Huang YA, You ZH, Chen X, Yan GY.
    BMC Syst Biol; 2016 Dec 23; 10(Suppl 4):120. PubMed ID: 28155718
    [Abstract] [Full Text] [Related]

  • 12. Using the Relevance Vector Machine Model Combined with Local Phase Quantization to Predict Protein-Protein Interactions from Protein Sequences.
    An JY, Meng FR, You ZH, Fang YH, Zhao YJ, Zhang M.
    Biomed Res Int; 2016 Dec 23; 2016():4783801. PubMed ID: 27314023
    [Abstract] [Full Text] [Related]

  • 13. Predicting protein-protein interactions from primary protein sequences using a novel multi-scale local feature representation scheme and the random forest.
    You ZH, Chan KC, Hu P.
    PLoS One; 2015 Dec 23; 10(5):e0125811. PubMed ID: 25946106
    [Abstract] [Full Text] [Related]

  • 14. Predicting protein-protein interactions from protein sequences by a stacked sparse autoencoder deep neural network.
    Wang YB, You ZH, Li X, Jiang TH, Chen X, Zhou X, Wang L.
    Mol Biosyst; 2017 Jun 27; 13(7):1336-1344. PubMed ID: 28604872
    [Abstract] [Full Text] [Related]

  • 15. Identification of self-interacting proteins by integrating random projection classifier and finite impulse response filter.
    Chen ZH, You ZH, Li LP, Wang YB, Qiu Y, Hu PW.
    BMC Genomics; 2019 Dec 27; 20(Suppl 13):928. PubMed ID: 31881833
    [Abstract] [Full Text] [Related]

  • 16. 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]

  • 17. Predicting protein-protein interactions by fusing various Chou's pseudo components and using wavelet denoising approach.
    Tian B, Wu X, Chen C, Qiu W, Ma Q, Yu B.
    J Theor Biol; 2019 Feb 07; 462():329-346. PubMed ID: 30452960
    [Abstract] [Full Text] [Related]

  • 18. Prediction of Protein-Protein Interactions from Amino Acid Sequences Based on Continuous and Discrete Wavelet Transform Features.
    Wang T, Li L, Huang YA, Zhang H, Ma Y, Zhou X.
    Molecules; 2018 Apr 04; 23(4):. PubMed ID: 29617272
    [Abstract] [Full Text] [Related]

  • 19. Detecting protein-protein interactions with a novel matrix-based protein sequence representation and support vector machines.
    You ZH, Li J, Gao X, He Z, Zhu L, Lei YK, Ji Z.
    Biomed Res Int; 2015 Apr 04; 2015():867516. PubMed ID: 26000305
    [Abstract] [Full Text] [Related]

  • 20. 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]

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