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Journal Abstract Search

161 related items for PubMed ID: 22575173

  • 1. Using machine learning techniques and genomic/proteomic information from known databases for defining relevant features for PPI classification.
    Urquiza JM, Rojas I, Pomares H, Herrera J, Florido JP, Valenzuela O, Cepero M.
    Comput Biol Med; 2012 Jun; 42(6):639-50. PubMed ID: 22575173
    [Abstract] [Full Text] [Related]

  • 2. Ranking support vector machine for multiple kernels output combination in protein-protein interaction extraction from biomedical literature.
    Yang Z, Lin Y, Wu J, Tang N, Lin H, Li Y.
    Proteomics; 2011 Oct; 11(19):3811-7. PubMed ID: 21834129
    [Abstract] [Full Text] [Related]

  • 3. Can simple codon pair usage predict protein-protein interaction?
    Zhou Y, Zhou YS, He F, Song J, Zhang Z.
    Mol Biosyst; 2012 Apr; 8(5):1396-404. PubMed ID: 22392100
    [Abstract] [Full Text] [Related]

  • 4. A mouse protein interactome through combined literature mining with multiple sources of interaction evidence.
    Li X, Cai H, Xu J, Ying S, Zhang Y.
    Amino Acids; 2010 Apr; 38(4):1237-52. PubMed ID: 19669079
    [Abstract] [Full Text] [Related]

  • 5. Functional genomics and proteomics in the clinical neurosciences: data mining and bioinformatics.
    Phan JH, Quo CF, Wang MD.
    Prog Brain Res; 2006 Apr; 158():83-108. PubMed ID: 17027692
    [Abstract] [Full Text] [Related]

  • 6. Predicting protein-protein interactions from protein sequences using meta predictor.
    Xia JF, Zhao XM, Huang DS.
    Amino Acids; 2010 Nov; 39(5):1595-9. PubMed ID: 20386937
    [Abstract] [Full Text] [Related]

  • 7. 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]

  • 8. 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]

  • 9. Detecting disease genes based on semi-supervised learning and protein-protein interaction networks.
    Nguyen TP, Ho TB.
    Artif Intell Med; 2012 Jan 04; 54(1):63-71. PubMed ID: 22000346
    [Abstract] [Full Text] [Related]

  • 10. FPPI: Fusarium graminearum protein-protein interaction database.
    Zhao XM, Zhang XW, Tang WH, Chen L.
    J Proteome Res; 2009 Oct 04; 8(10):4714-21. PubMed ID: 19673500
    [Abstract] [Full Text] [Related]

  • 11. Mixture classification model based on clinical markers for breast cancer prognosis.
    Zeng T, Liu J.
    Artif Intell Med; 2010 Oct 04; 48(2-3):129-37. PubMed ID: 20005686
    [Abstract] [Full Text] [Related]

  • 12. Prediction of biological protein-protein interactions using atom-type and amino acid properties.
    Aziz MM, Maleki M, Rueda L, Raza M, Banerjee S.
    Proteomics; 2011 Oct 04; 11(19):3802-10. PubMed ID: 21789780
    [Abstract] [Full Text] [Related]

  • 13. Adaptive compressive learning for prediction of protein-protein interactions from primary sequence.
    Zhang YN, Pan XY, Huang Y, Shen HB.
    J Theor Biol; 2011 Aug 21; 283(1):44-52. PubMed ID: 21635901
    [Abstract] [Full Text] [Related]

  • 14. Ensemble learning prediction of protein-protein interactions using proteins functional annotations.
    Saha I, Zubek J, Klingström T, Forsberg S, Wikander J, Kierczak M, Maulik U, Plewczynski D.
    Mol Biosyst; 2014 Apr 21; 10(4):820-30. PubMed ID: 24469380
    [Abstract] [Full Text] [Related]

  • 15. A machine learning-based approach to prognostic analysis of thoracic transplantations.
    Delen D, Oztekin A, Kong ZJ.
    Artif Intell Med; 2010 May 21; 49(1):33-42. PubMed ID: 20153956
    [Abstract] [Full Text] [Related]

  • 16. Filter versus wrapper gene selection approaches in DNA microarray domains.
    Inza I, Larrañaga P, Blanco R, Cerrolaza AJ.
    Artif Intell Med; 2004 Jun 21; 31(2):91-103. PubMed ID: 15219288
    [Abstract] [Full Text] [Related]

  • 17. Biomedical events extraction using the hidden vector state model.
    Zhou D, He Y.
    Artif Intell Med; 2011 Nov 21; 53(3):205-13. PubMed ID: 21945347
    [Abstract] [Full Text] [Related]

  • 18. AVID: an integrative framework for discovering functional relationships among proteins.
    Jiang T, Keating AE.
    BMC Bioinformatics; 2005 Jun 01; 6():136. PubMed ID: 15929793
    [Abstract] [Full Text] [Related]

  • 19. Heterogeneous data integration by tree-augmented naïve Bayes for protein-protein interactions prediction.
    Lin X, Chen XW.
    Proteomics; 2013 Jan 01; 13(2):261-8. PubMed ID: 23112070
    [Abstract] [Full Text] [Related]

  • 20. Detecting reliable non interacting proteins (NIPs) significantly enhancing the computational prediction of protein-protein interactions using machine learning methods.
    Srivastava A, Mazzocco G, Kel A, Wyrwicz LS, Plewczynski D.
    Mol Biosyst; 2016 Mar 01; 12(3):778-85. PubMed ID: 26738778
    [Abstract] [Full Text] [Related]

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