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

458 related items for PubMed ID: 30598096

  • 1. Predicting protein-protein interactions using high-quality non-interacting pairs.
    Zhang L, Yu G, Guo M, Wang J.
    BMC Bioinformatics; 2018 Dec 31; 19(Suppl 19):525. PubMed ID: 30598096
    [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. Protein-Protein Interactions Prediction Using a Novel Local Conjoint Triad Descriptor of Amino Acid Sequences.
    Wang J, Zhang L, Jia L, Ren Y, Yu G.
    Int J Mol Sci; 2017 Nov 08; 18(11):. PubMed ID: 29117139
    [Abstract] [Full Text] [Related]

  • 4. SDNN-PPI: self-attention with deep neural network effect on protein-protein interaction prediction.
    Li X, Han P, Wang G, Chen W, Wang S, Song T.
    BMC Genomics; 2022 Jun 27; 23(1):474. PubMed ID: 35761175
    [Abstract] [Full Text] [Related]

  • 5. 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 Jun 27; 10(5):e0125811. PubMed ID: 25946106
    [Abstract] [Full Text] [Related]

  • 6. 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]

  • 7. A Cascade Random Forests Algorithm for Predicting Protein-Protein Interaction Sites.
    Wei ZS, Yang JY, Shen HB, Yu DJ.
    IEEE Trans Nanobioscience; 2015 Oct 23; 14(7):746-60. PubMed ID: 26441427
    [Abstract] [Full Text] [Related]

  • 8. Prediction of protein-protein interactions based on PseAA composition and hybrid feature selection.
    Liu L, Cai Y, Lu W, Feng K, Peng C, Niu B.
    Biochem Biophys Res Commun; 2009 Mar 06; 380(2):318-22. PubMed ID: 19171120
    [Abstract] [Full Text] [Related]

  • 9. DeepPPI: Boosting Prediction of Protein-Protein Interactions with Deep Neural Networks.
    Du X, Sun S, Hu C, Yao Y, Yan Y, Zhang Y.
    J Chem Inf Model; 2017 Jun 26; 57(6):1499-1510. PubMed ID: 28514151
    [Abstract] [Full Text] [Related]

  • 10. Prediction of protein-protein interactions from amino acid sequences using a novel multi-scale continuous and discontinuous feature set.
    You ZH, Zhu L, Zheng CH, Yu HJ, Deng SP, Ji Z.
    BMC Bioinformatics; 2014 Jun 26; 15 Suppl 15(Suppl 15):S9. PubMed ID: 25474679
    [Abstract] [Full Text] [Related]

  • 11. 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]

  • 12. Prediction of Protein-Protein Interaction via co-occurring Aligned Pattern Clusters.
    Sze-To A, Fung S, Lee EA, Wong AKC.
    Methods; 2016 Nov 01; 110():26-34. PubMed ID: 27476008
    [Abstract] [Full Text] [Related]

  • 13. Comparative analysis and assessment of M. tuberculosis H37Rv protein-protein interaction datasets.
    Zhou H, Wong L.
    BMC Genomics; 2011 Nov 30; 12 Suppl 3(Suppl 3):S20. PubMed ID: 22369691
    [Abstract] [Full Text] [Related]

  • 14. 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]

  • 15. Homology-based prediction of interactions between proteins using Averaged One-Dependence Estimators.
    Murakami Y, Mizuguchi K.
    BMC Bioinformatics; 2014 Jun 23; 15():213. PubMed ID: 24953126
    [Abstract] [Full Text] [Related]

  • 16. Using support vector machine combined with auto covariance to predict protein-protein interactions from protein sequences.
    Guo Y, Yu L, Wen Z, Li M.
    Nucleic Acids Res; 2008 May 23; 36(9):3025-30. PubMed ID: 18390576
    [Abstract] [Full Text] [Related]

  • 17. 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 May 23; 2022():7191684. PubMed ID: 35242211
    [Abstract] [Full Text] [Related]

  • 18. 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]

  • 19. 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]

  • 20. Identification of Protein-Protein Interactions via a Novel Matrix-Based Sequence Representation Model with Amino Acid Contact Information.
    Ding Y, Tang J, Guo F.
    Int J Mol Sci; 2016 Sep 24; 17(10):. PubMed ID: 27669239
    [Abstract] [Full Text] [Related]

    Page: [Next] [New Search]
    of 23.