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Journal Abstract Search

783 related items for PubMed ID: 30071670

  • 1. Deep Neural Network Based Predictions of Protein Interactions Using Primary Sequences.
    Li H, Gong XJ, Yu H, Zhou C.
    Molecules; 2018 Aug 01; 23(8):. PubMed ID: 30071670
    [Abstract] [Full Text] [Related]

  • 2. 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]

  • 3. Graph-based prediction of Protein-protein interactions with attributed signed graph embedding.
    Yang F, Fan K, Song D, Lin H.
    BMC Bioinformatics; 2020 Jul 21; 21(1):323. PubMed ID: 32693790
    [Abstract] [Full Text] [Related]

  • 4. Completing sparse and disconnected protein-protein network by deep learning.
    Huang L, Liao L, Wu CH.
    BMC Bioinformatics; 2018 Mar 22; 19(1):103. PubMed ID: 29566671
    [Abstract] [Full Text] [Related]

  • 5. Sequence-based prediction of protein protein interaction using a deep-learning algorithm.
    Sun T, Zhou B, Lai L, Pei J.
    BMC Bioinformatics; 2017 May 25; 18(1):277. PubMed ID: 28545462
    [Abstract] [Full Text] [Related]

  • 6. AE-LGBM: Sequence-based novel approach to detect interacting protein pairs via ensemble of autoencoder and LightGBM.
    Sharma A, Singh B.
    Comput Biol Med; 2020 Oct 25; 125():103964. PubMed ID: 32911276
    [Abstract] [Full Text] [Related]

  • 7. Prediction of Protein-Protein Interactions Based on Integrating Deep Learning and Feature Fusion.
    Tran HN, Nguyen PX, Guo F, Wang J.
    Int J Mol Sci; 2024 May 27; 25(11):. PubMed ID: 38892007
    [Abstract] [Full Text] [Related]

  • 8. 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]

  • 9. Multimodal deep representation learning for protein interaction identification and protein family classification.
    Zhang D, Kabuka M.
    BMC Bioinformatics; 2019 Dec 02; 20(Suppl 16):531. PubMed ID: 31787089
    [Abstract] [Full Text] [Related]

  • 10. MaTPIP: A deep-learning architecture with eXplainable AI for sequence-driven, feature mixed protein-protein interaction prediction.
    Ghosh S, Mitra P.
    Comput Methods Programs Biomed; 2024 Feb 02; 244():107955. PubMed ID: 38064959
    [Abstract] [Full Text] [Related]

  • 11. 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]

  • 12. 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]

  • 13. 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]

  • 14. HN-PPISP: a hybrid network based on MLP-Mixer for protein-protein interaction site prediction.
    Kang Y, Xu Y, Wang X, Pu B, Yang X, Rao Y, Chen J.
    Brief Bioinform; 2023 Jan 19; 24(1):. PubMed ID: 36403092
    [Abstract] [Full Text] [Related]

  • 15. Predicting protein-ligand binding residues with deep convolutional neural networks.
    Cui Y, Dong Q, Hong D, Wang X.
    BMC Bioinformatics; 2019 Feb 26; 20(1):93. PubMed ID: 30808287
    [Abstract] [Full Text] [Related]

  • 16.
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  • 17. DeepACLSTM: deep asymmetric convolutional long short-term memory neural models for protein secondary structure prediction.
    Guo Y, Li W, Wang B, Liu H, Zhou D.
    BMC Bioinformatics; 2019 Jun 17; 20(1):341. PubMed ID: 31208331
    [Abstract] [Full Text] [Related]

  • 18. DL-PPI: a method on prediction of sequenced protein-protein interaction based on deep learning.
    Wu J, Liu B, Zhang J, Wang Z, Li J.
    BMC Bioinformatics; 2023 Dec 14; 24(1):473. PubMed ID: 38097937
    [Abstract] [Full Text] [Related]

  • 19. An Investigation of Deep Learning Models for EEG-Based Emotion Recognition.
    Zhang Y, Chen J, Tan JH, Chen Y, Chen Y, Li D, Yang L, Su J, Huang X, Che W.
    Front Neurosci; 2020 Dec 14; 14():622759. PubMed ID: 33424547
    [Abstract] [Full Text] [Related]

  • 20. Long short-term memory neural network for air pollutant concentration predictions: Method development and evaluation.
    Li X, Peng L, Yao X, Cui S, Hu Y, You C, Chi T.
    Environ Pollut; 2017 Dec 14; 231(Pt 1):997-1004. PubMed ID: 28898956
    [Abstract] [Full Text] [Related]

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