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Journal Abstract Search

281 related items for PubMed ID: 16872538

  • 1. PIPE: a protein-protein interaction prediction engine based on the re-occurring short polypeptide sequences between known interacting protein pairs.
    Pitre S, Dehne F, Chan A, Cheetham J, Duong A, Emili A, Gebbia M, Greenblatt J, Jessulat M, Krogan N, Luo X, Golshani A.
    BMC Bioinformatics; 2006 Jul 27; 7():365. PubMed ID: 16872538
    [Abstract] [Full Text] [Related]

  • 2. Binding site prediction for protein-protein interactions and novel motif discovery using re-occurring polypeptide sequences.
    Amos-Binks A, Patulea C, Pitre S, Schoenrock A, Gui Y, Green JR, Golshani A, Dehne F.
    BMC Bioinformatics; 2011 Jun 02; 12():225. PubMed ID: 21635751
    [Abstract] [Full Text] [Related]

  • 3. Global investigation of protein-protein interactions in yeast Saccharomyces cerevisiae using re-occurring short polypeptide sequences.
    Pitre S, North C, Alamgir M, Jessulat M, Chan A, Luo X, Green JR, Dumontier M, Dehne F, Golshani A.
    Nucleic Acids Res; 2008 Aug 02; 36(13):4286-94. PubMed ID: 18586826
    [Abstract] [Full Text] [Related]

  • 4. GAIA: a gram-based interaction analysis tool--an approach for identifying interacting domains in yeast.
    Zhang KX, Ouellette BF.
    BMC Bioinformatics; 2009 Jan 30; 10 Suppl 1(Suppl 1):S60. PubMed ID: 19208164
    [Abstract] [Full Text] [Related]

  • 5. 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]

  • 6. Bootstrapping the interactome: unsupervised identification of protein complexes in yeast.
    Friedel CC, Krumsiek J, Zimmer R.
    J Comput Biol; 2009 Aug 01; 16(8):971-87. PubMed ID: 19630542
    [Abstract] [Full Text] [Related]

  • 7. 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]

  • 8. A novel approach to investigating protein/protein interactions and their functions by TAP-tagged yeast strains and its application to examine yeast transcription machinery.
    Jung J, Ahn YJ, Kang LW.
    J Microbiol Biotechnol; 2008 Apr 12; 18(4):631-8. PubMed ID: 18467854
    [Abstract] [Full Text] [Related]

  • 9. Structure-based prediction of protein-protein interactions on a genome-wide scale.
    Zhang QC, Petrey D, Deng L, Qiang L, Shi Y, Thu CA, Bisikirska B, Lefebvre C, Accili D, Hunter T, Maniatis T, Califano A, Honig B.
    Nature; 2012 Oct 25; 490(7421):556-60. PubMed ID: 23023127
    [Abstract] [Full Text] [Related]

  • 10. A Bayesian networks approach for predicting protein-protein interactions from genomic data.
    Jansen R, Yu H, Greenbaum D, Kluger Y, Krogan NJ, Chung S, Emili A, Snyder M, Greenblatt JF, Gerstein M.
    Science; 2003 Oct 17; 302(5644):449-53. PubMed ID: 14564010
    [Abstract] [Full Text] [Related]

  • 11. Quantitative assessment of the structural bias in protein-protein interaction assays.
    Björklund AK, Light S, Hedin L, Elofsson A.
    Proteomics; 2008 Nov 17; 8(22):4657-67. PubMed ID: 18924110
    [Abstract] [Full Text] [Related]

  • 12. Pushing structural information into the yeast interactome by high-throughput protein docking experiments.
    Mosca R, Pons C, Fernández-Recio J, Aloy P.
    PLoS Comput Biol; 2009 Aug 17; 5(8):e1000490. PubMed ID: 19714207
    [Abstract] [Full Text] [Related]

  • 13. A combined experimental and computational strategy to define protein interaction networks for peptide recognition modules.
    Tong AH, Drees B, Nardelli G, Bader GD, Brannetti B, Castagnoli L, Evangelista M, Ferracuti S, Nelson B, Paoluzi S, Quondam M, Zucconi A, Hogue CW, Fields S, Boone C, Cesareni G.
    Science; 2002 Jan 11; 295(5553):321-4. PubMed ID: 11743162
    [Abstract] [Full Text] [Related]

  • 14. The Cross-and-Capture system: a versatile tool in yeast proteomics.
    Suter B.
    Methods; 2012 Dec 11; 58(4):360-6. PubMed ID: 22836129
    [Abstract] [Full Text] [Related]

  • 15. Identifying conserved protein complexes between species by constructing interolog networks.
    Nguyen PV, Srihari S, Leong HW.
    BMC Bioinformatics; 2013 Dec 11; 14 Suppl 16(Suppl 16):S8. PubMed ID: 24564762
    [Abstract] [Full Text] [Related]

  • 16. Computational Analysis of the Chaperone Interaction Networks.
    Kumar A, Rizzolo K, Zilles S, Babu M, Houry WA.
    Methods Mol Biol; 2018 Dec 11; 1709():275-291. PubMed ID: 29177666
    [Abstract] [Full Text] [Related]

  • 17. Genome-scale gene function prediction using multiple sources of high-throughput data in yeast Saccharomyces cerevisiae.
    Joshi T, Chen Y, Becker JM, Alexandrov N, Xu D.
    OMICS; 2004 Dec 11; 8(4):322-33. PubMed ID: 15703479
    [Abstract] [Full Text] [Related]

  • 18. A lock-and-key model for protein-protein interactions.
    Morrison JL, Breitling R, Higham DJ, Gilbert DR.
    Bioinformatics; 2006 Aug 15; 22(16):2012-9. PubMed ID: 16787977
    [Abstract] [Full Text] [Related]

  • 19. Filtering high-throughput protein-protein interaction data using a combination of genomic features.
    Patil A, Nakamura H.
    BMC Bioinformatics; 2005 Apr 18; 6():100. PubMed ID: 15833142
    [Abstract] [Full Text] [Related]

  • 20. Applicability of tandem affinity purification MudPIT to pathway proteomics in yeast.
    Graumann J, Dunipace LA, Seol JH, McDonald WH, Yates JR, Wold BJ, Deshaies RJ.
    Mol Cell Proteomics; 2004 Mar 18; 3(3):226-37. PubMed ID: 14660704
    [Abstract] [Full Text] [Related]

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