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Journal Abstract Search

328 related items for PubMed ID: 22587966

  • 1. Mycobacterium tuberculosis and Clostridium difficille interactomes: demonstration of rapid development of computational system for bacterial interactome prediction.
    Ananthasubramanian S, Metri R, Khetan A, Gupta A, Handen A, Chandra N, Ganapathiraju M.
    Microb Inform Exp; 2012 Mar 21; 2():4. PubMed ID: 22587966
    [Abstract] [Full Text] [Related]

  • 2. Comparative analysis and assessment of M. tuberculosis H37Rv protein-protein interaction datasets.
    Zhou H, Wong L.
    BMC Genomics; 2011 Nov 30; 12 Suppl 3(Suppl 3):S20. PubMed ID: 22369691
    [Abstract] [Full Text] [Related]

  • 3. Bacterial protein meta-interactomes predict cross-species interactions and protein function.
    Caufield JH, Wimble C, Shary S, Wuchty S, Uetz P.
    BMC Bioinformatics; 2017 Mar 16; 18(1):171. PubMed ID: 28298180
    [Abstract] [Full Text] [Related]

  • 4. Complementing the Eukaryotic Protein Interactome.
    Pesch R, Zimmer R.
    PLoS One; 2013 Mar 16; 8(6):e66635. PubMed ID: 23825550
    [Abstract] [Full Text] [Related]

  • 5.
    ; 2004 Mar 16. PubMed ID: 33001599
    [Abstract] [Full Text] [Related]

  • 6. Predicting gene ontology annotations of orphan GWAS genes using protein-protein interactions.
    Kuppuswamy U, Ananthasubramanian S, Wang Y, Balakrishnan N, Ganapathiraju MK.
    Algorithms Mol Biol; 2014 Apr 03; 9(1):10. PubMed ID: 24708602
    [Abstract] [Full Text] [Related]

  • 7. Predicting whole genome protein interaction networks from primary sequence data in model and non-model organisms using ENTS.
    Rodgers-Melnick E, Culp M, DiFazio SP.
    BMC Genomics; 2013 Sep 10; 14():608. PubMed ID: 24015873
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  • 8. Schizophrenia interactome with 504 novel protein-protein interactions.
    Ganapathiraju MK, Thahir M, Handen A, Sarkar SN, Sweet RA, Nimgaonkar VL, Loscher CE, Bauer EM, Chaparala S.
    NPJ Schizophr; 2016 Sep 10; 2():16012. PubMed ID: 27336055
    [Abstract] [Full Text] [Related]

  • 9. Using structural knowledge in the protein data bank to inform the search for potential host-microbe protein interactions in sequence space: application to Mycobacterium tuberculosis.
    Mahajan G, Mande SC.
    BMC Bioinformatics; 2017 Apr 04; 18(1):201. PubMed ID: 28376709
    [Abstract] [Full Text] [Related]

  • 10. Improving the Detection of Protein Complexes by Predicting Novel Missing Interactome Links in the Protein-Protein Interaction Network.
    Zaki N, Alashwal H.
    Annu Int Conf IEEE Eng Med Biol Soc; 2018 Jul 04; 2018():5041-5044. PubMed ID: 30441473
    [Abstract] [Full Text] [Related]

  • 11. [Development of antituberculous drugs: current status and future prospects].
    Tomioka H, Namba K.
    Kekkaku; 2006 Dec 04; 81(12):753-74. PubMed ID: 17240921
    [Abstract] [Full Text] [Related]

  • 12. Editorial: Current status and perspective on drug targets in tubercle bacilli and drug design of antituberculous agents based on structure-activity relationship.
    Tomioka H.
    Curr Pharm Des; 2014 Dec 04; 20(27):4305-6. PubMed ID: 24245755
    [Abstract] [Full Text] [Related]

  • 13. Gene function finding through cross-organism ensemble learning.
    Moro G, Masseroli M.
    BioData Min; 2021 Feb 12; 14(1):14. PubMed ID: 33579334
    [Abstract] [Full Text] [Related]

  • 14. Cross-organism learning method to discover new gene functionalities.
    Domeniconi G, Masseroli M, Moro G, Pinoli P.
    Comput Methods Programs Biomed; 2016 Apr 12; 126():20-34. PubMed ID: 26724853
    [Abstract] [Full Text] [Related]

  • 15. Transferring knowledge of bacterial protein interaction networks to predict pathogen targeted human genes and immune signaling pathways: a case study on M. tuberculosis.
    Mei S, Flemington EK, Zhang K.
    BMC Genomics; 2018 Jun 28; 19(1):505. PubMed ID: 29954330
    [Abstract] [Full Text] [Related]

  • 16. Predicting the interactome of Xanthomonas oryzae pathovar oryzae for target selection and DB service.
    Kim JG, Park D, Kim BC, Cho SW, Kim YT, Park YJ, Cho HJ, Park H, Kim KB, Yoon KO, Park SJ, Lee BM, Bhak J.
    BMC Bioinformatics; 2008 Jan 24; 9():41. PubMed ID: 18215330
    [Abstract] [Full Text] [Related]

  • 17. Network-based features enable prediction of essential genes across diverse organisms.
    Azhagesan K, Ravindran B, Raman K.
    PLoS One; 2018 Jan 24; 13(12):e0208722. PubMed ID: 30543651
    [Abstract] [Full Text] [Related]

  • 18. Genome-wide inference of the Camponotus floridanus protein-protein interaction network using homologous mapping and interacting domain profile pairs.
    Gupta SK, Srivastava M, Osmanoglu Ö, Dandekar T.
    Sci Rep; 2020 Feb 11; 10(1):2334. PubMed ID: 32047225
    [Abstract] [Full Text] [Related]

  • 19. 3D-interologs: an evolution database of physical protein- protein interactions across multiple genomes.
    Lo YS, Chen YC, Yang JM.
    BMC Genomics; 2010 Dec 01; 11 Suppl 3(Suppl 3):S7. PubMed ID: 21143789
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  • 20. Prediction of evolutionarily conserved interologs in Mus musculus.
    Yellaboina S, Dudekula DB, Ko MSh.
    BMC Genomics; 2008 Oct 08; 9():465. PubMed ID: 18842131
    [Abstract] [Full Text] [Related]

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