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Journal Abstract Search

211 related items for PubMed ID: 27849060

  • 1. Large-scale identification of human protein function using topological features of interaction network.
    Li Z, Liu Z, Zhong W, Huang M, Wu N, Xie Y, Dai Z, Zou X.
    Sci Rep; 2016 Nov 16; 6():37179. PubMed ID: 27849060
    [Abstract] [Full Text] [Related]

  • 2. Identification of human protein complexes from local sub-graphs of protein-protein interaction network based on random forest with topological structure features.
    Li ZC, Lai YH, Chen LL, Zhou X, Dai Z, Zou XY.
    Anal Chim Acta; 2012 Mar 09; 718():32-41. PubMed ID: 22305895
    [Abstract] [Full Text] [Related]

  • 3. Large-scale identification of potential drug targets based on the topological features of human protein-protein interaction network.
    Li ZC, Zhong WQ, Liu ZQ, Huang MH, Xie Y, Dai Z, Zou XY.
    Anal Chim Acta; 2015 Apr 29; 871():18-27. PubMed ID: 25847157
    [Abstract] [Full Text] [Related]

  • 4. Fitting a geometric graph to a protein-protein interaction network.
    Higham DJ, Rasajski M, Przulj N.
    Bioinformatics; 2008 Apr 15; 24(8):1093-9. PubMed ID: 18344248
    [Abstract] [Full Text] [Related]

  • 5. Improving protein protein interaction prediction based on phylogenetic information using a least-squares support vector machine.
    Craig RA, Liao L.
    Ann N Y Acad Sci; 2007 Dec 15; 1115():154-67. PubMed ID: 17925357
    [Abstract] [Full Text] [Related]

  • 6. Whole-proteome prediction of protein function via graph-theoretic analysis of interaction maps.
    Nabieva E, Jim K, Agarwal A, Chazelle B, Singh M.
    Bioinformatics; 2005 Jun 15; 21 Suppl 1():i302-10. PubMed ID: 15961472
    [Abstract] [Full Text] [Related]

  • 7. Identification of protein complexes from multi-relationship protein interaction networks.
    Li X, Wang J, Zhao B, Wu FX, Pan Y.
    Hum Genomics; 2016 Jul 25; 10 Suppl 2(Suppl 2):17. PubMed ID: 27461193
    [Abstract] [Full Text] [Related]

  • 8. 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 Jul 25; 10(5):e0125811. PubMed ID: 25946106
    [Abstract] [Full Text] [Related]

  • 9. BMRF-MI: integrative identification of protein interaction network by modeling the gene dependency.
    Shi X, Wang X, Shajahan A, Hilakivi-Clarke L, Clarke R, Xuan J.
    BMC Genomics; 2015 Jul 25; 16 Suppl 7(Suppl 7):S10. PubMed ID: 26099273
    [Abstract] [Full Text] [Related]

  • 10. [The study on the characters of membrane protein interaction and its network based on integrated intelligence method].
    Shen Y, Ding Y, Hao K.
    Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 2011 Aug 25; 28(4):658-62. PubMed ID: 21936357
    [Abstract] [Full Text] [Related]

  • 11. Predicting domain-domain interaction based on domain profiles with feature selection and support vector machines.
    González AJ, Liao L.
    BMC Bioinformatics; 2010 Oct 29; 11():537. PubMed ID: 21034480
    [Abstract] [Full Text] [Related]

  • 12. Identifying protein complexes using hybrid properties.
    Chen L, Shi X, Kong X, Zeng Z, Cai YD.
    J Proteome Res; 2009 Nov 29; 8(11):5212-8. PubMed ID: 19764809
    [Abstract] [Full Text] [Related]

  • 13. A Topology Potential-Based Method for Identifying Essential Proteins from PPI Networks.
    Li M, Lu Y, Wang J, Wu FX, Pan Y.
    IEEE/ACM Trans Comput Biol Bioinform; 2015 Nov 29; 12(2):372-83. PubMed ID: 26357224
    [Abstract] [Full Text] [Related]

  • 14. Topology of functional networks predicts physical binding of proteins.
    Saraç OS, Pancaldi V, Bähler J, Beyer A.
    Bioinformatics; 2012 Aug 15; 28(16):2137-45. PubMed ID: 22718785
    [Abstract] [Full Text] [Related]

  • 15. Information theory applied to the sparse gene ontology annotation network to predict novel gene function.
    Tao Y, Sam L, Li J, Friedman C, Lussier YA.
    Bioinformatics; 2007 Jul 01; 23(13):i529-38. PubMed ID: 17646340
    [Abstract] [Full Text] [Related]

  • 16. Analysis and identification of essential genes in humans using topological properties and biological information.
    Yang L, Wang J, Wang H, Lv Y, Zuo Y, Li X, Jiang W.
    Gene; 2014 Nov 10; 551(2):138-51. PubMed ID: 25168893
    [Abstract] [Full Text] [Related]

  • 17. Automated feature engineering improves prediction of protein-protein interactions.
    Sumonja N, Gemovic B, Veljkovic N, Perovic V.
    Amino Acids; 2019 Aug 10; 51(8):1187-1200. PubMed ID: 31278492
    [Abstract] [Full Text] [Related]

  • 18. Identifying and prioritizing disease-related genes based on the network topological features.
    Li ZC, Lai YH, Chen LL, Xie Y, Dai Z, Zou XY.
    Biochim Biophys Acta; 2014 Dec 10; 1844(12):2214-21. PubMed ID: 25183318
    [Abstract] [Full Text] [Related]

  • 19. Improving hot region prediction by parameter optimization of density clustering in PPI.
    Hu J, Zhang X.
    Methods; 2016 Nov 01; 110():35-43. PubMed ID: 27474164
    [Abstract] [Full Text] [Related]

  • 20. 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]

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