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Journal Abstract Search

191 related items for PubMed ID: 38741045

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  • 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
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  • 5. Protein-Protein Interactions Prediction Based on Graph Energy and Protein Sequence Information.
    Xu D, Xu H, Zhang Y, Chen W, Gao R.
    Molecules; 2020 Apr 16; 25(8):. PubMed ID: 32316294
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  • 7. Using Weighted Extreme Learning Machine Combined With Scale-Invariant Feature Transform to Predict Protein-Protein Interactions From Protein Evolutionary Information.
    Li J, Shi X, You ZH, Yi HC, Chen Z, Lin Q, Fang M.
    IEEE/ACM Trans Comput Biol Bioinform; 2020 Apr 16; 17(5):1546-1554. PubMed ID: 31940546
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  • 9. 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
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  • 11. 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 23; 25(10):1825-33. PubMed ID: 27452983
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  • 12. Sequence-based prediction of protein-protein interactions using weighted sparse representation model combined with global encoding.
    Huang YA, You ZH, Chen X, Chan K, Luo X.
    BMC Bioinformatics; 2016 Apr 26; 17(1):184. PubMed ID: 27112932
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  • 13. 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
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  • 14. 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 Feb 07; 14 Suppl 8(Suppl 8):S10. PubMed ID: 23815620
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  • 15. DSSGNN-PPI: A Protein-Protein Interactions prediction model based on Double Structure and Sequence graph neural networks.
    Zhang F, Chang S, Wang B, Zhang X.
    Comput Biol Med; 2024 Jul 07; 177():108669. PubMed ID: 38833802
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  • 16. 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
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  • 17. Amalgamation of 3D structure and sequence information for protein-protein interaction prediction.
    Jha K, Saha S.
    Sci Rep; 2020 Nov 05; 10(1):19171. PubMed ID: 33154416
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  • 18. 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
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  • 19. Improved Prediction of Protein-Protein Interaction Mapping on Homo Sapiens by Using Amino Acid Sequence Features in a Supervised Learning Framework.
    Islam MM, Alam MJ, Ahmed FF, Hasan MM, Mollah MNH.
    Protein Pept Lett; 2021 Aug 18; 28(1):74-83. PubMed ID: 32520672
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  • 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
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