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Journal Abstract Search

516 related items for PubMed ID: 25474679

  • 21. 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
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  • 22. Predicting protein-protein interactions by combing various sequence- derived features into the general form of Chou's Pseudo amino acid composition.
    Zhao XW, Ma ZQ, Yin MH.
    Protein Pept Lett; 2012 May 07; 19(5):492-500. PubMed ID: 22486644
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  • 24. 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
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  • 27. 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
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  • 29. 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 Aug 25; 2016():4783801. PubMed ID: 27314023
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  • 30. An Efficient Feature Extraction Technique Based on Local Coding PSSM and Multifeatures Fusion for Predicting Protein-Protein Interactions.
    An JY, Zhou Y, Zhao YJ, Yan ZJ.
    Evol Bioinform Online; 2019 Aug 25; 15():1176934319879920. PubMed ID: 31619921
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  • 31. A discriminative approach for identifying domain-domain interactions from protein-protein interactions.
    Zhao XM, Chen L, Aihara K.
    Proteins; 2010 Apr 25; 78(5):1243-53. PubMed ID: 20027642
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  • 33. 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
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  • 36. Prediction of nuclear proteins using nuclear translocation signals proposed by probabilistic latent semantic indexing.
    Su EC, Chang JM, Cheng CW, Sung TY, Hsu WL.
    BMC Bioinformatics; 2012 Dec 24; 13 Suppl 17(Suppl 17):S13. PubMed ID: 23282098
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  • 37. 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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  • 38. 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
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