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Journal Abstract Search

228 related items for PubMed ID: 22369691

  • 1. 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]

  • 2. Stringent DDI-based prediction of H. sapiens-M. tuberculosis H37Rv protein-protein interactions.
    Zhou H, Rezaei J, Hugo W, Gao S, Jin J, Fan M, Yong CH, Wozniak M, Wong L.
    BMC Syst Biol; 2013 Nov 30; 7 Suppl 6(Suppl 6):S6. PubMed ID: 24564941
    [Abstract] [Full Text] [Related]

  • 3. Stringent homology-based prediction of H. sapiens-M. tuberculosis H37Rv protein-protein interactions.
    Zhou H, Gao S, Nguyen NN, Fan M, Jin J, Liu B, Zhao L, Xiong G, Tan M, Li S, Wong L.
    Biol Direct; 2014 Apr 08; 9():5. PubMed ID: 24708540
    [Abstract] [Full Text] [Related]

  • 4. 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]

  • 5. Global protein-protein interaction network in the human pathogen Mycobacterium tuberculosis H37Rv.
    Wang Y, Cui T, Zhang C, Yang M, Huang Y, Li W, Zhang L, Gao C, He Y, Li Y, Huang F, Zeng J, Huang C, Yang Q, Tian Y, Zhao C, Chen H, Zhang H, He ZG.
    J Proteome Res; 2010 Dec 03; 9(12):6665-77. PubMed ID: 20973567
    [Abstract] [Full Text] [Related]

  • 6. Assembling a protein-protein interaction map of the SSU processome from existing datasets.
    Lim YH, Charette JM, Baserga SJ.
    PLoS One; 2011 Mar 10; 6(3):e17701. PubMed ID: 21423703
    [Abstract] [Full Text] [Related]

  • 7. False positive reduction in protein-protein interaction predictions using gene ontology annotations.
    Mahdavi MA, Lin YH.
    BMC Bioinformatics; 2007 Jul 23; 8():262. PubMed ID: 17645798
    [Abstract] [Full Text] [Related]

  • 8. MCL-CAw: a refinement of MCL for detecting yeast complexes from weighted PPI networks by incorporating core-attachment structure.
    Srihari S, Ning K, Leong HW.
    BMC Bioinformatics; 2010 Oct 12; 11():504. PubMed ID: 20939868
    [Abstract] [Full Text] [Related]

  • 9. MEGADOCK-Web: an integrated database of high-throughput structure-based protein-protein interaction predictions.
    Hayashi T, Matsuzaki Y, Yanagisawa K, Ohue M, Akiyama Y.
    BMC Bioinformatics; 2018 May 08; 19(Suppl 4):62. PubMed ID: 29745830
    [Abstract] [Full Text] [Related]

  • 10. 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
    [Abstract] [Full Text] [Related]

  • 11. PPIDomainMiner: Inferring domain-domain interactions from multiple sources of protein-protein interactions.
    Alborzi SZ, Ahmed Nacer A, Najjar H, Ritchie DW, Devignes MD.
    PLoS Comput Biol; 2021 Aug 31; 17(8):e1008844. PubMed ID: 34370723
    [Abstract] [Full Text] [Related]

  • 12. An improved method for scoring protein-protein interactions using semantic similarity within the gene ontology.
    Jain S, Bader GD.
    BMC Bioinformatics; 2010 Nov 15; 11():562. PubMed ID: 21078182
    [Abstract] [Full Text] [Related]

  • 13. Computational probing protein-protein interactions targeting small molecules.
    Wang YC, Chen SL, Deng NY, Wang Y.
    Bioinformatics; 2016 Jan 15; 32(2):226-34. PubMed ID: 26415726
    [Abstract] [Full Text] [Related]

  • 14. HAPPI: an online database of comprehensive human annotated and predicted protein interactions.
    Chen JY, Mamidipalli S, Huan T.
    BMC Genomics; 2009 Jul 07; 10 Suppl 1(Suppl 1):S16. PubMed ID: 19594875
    [Abstract] [Full Text] [Related]

  • 15. Uncovering New Pathogen-Host Protein-Protein Interactions by Pairwise Structure Similarity.
    Cui T, Li W, Liu L, Huang Q, He ZG.
    PLoS One; 2016 Jul 07; 11(1):e0147612. PubMed ID: 26799490
    [Abstract] [Full Text] [Related]

  • 16. 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]

  • 17. 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]

  • 18. Making the Right Choice: Critical Parameters of the Y2H Systems.
    Mehla J, Caufield JH, Uetz P.
    Methods Mol Biol; 2018 May 18; 1794():17-28. PubMed ID: 29855948
    [Abstract] [Full Text] [Related]

  • 19. Unraveling the conundrum of seemingly discordant protein-protein interaction datasets.
    Gupta S, Wallqvist A, Bondugula R, Ivanic J, Reifman J.
    Annu Int Conf IEEE Eng Med Biol Soc; 2010 May 18; 2010():783-6. PubMed ID: 21096109
    [Abstract] [Full Text] [Related]

  • 20. Comparative transcriptomic analysis of THP-1-derived macrophages infected with Mycobacterium tuberculosis H37Rv, H37Ra and BCG.
    Pu W, Zhao C, Wazir J, Su Z, Niu M, Song S, Wei L, Li L, Zhang X, Shi X, Wang H.
    J Cell Mol Med; 2021 Nov 18; 25(22):10504-10520. PubMed ID: 34632719
    [Abstract] [Full Text] [Related]

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