Warning: The NCBI web site requires JavaScript to function. more...
Making the most of high-throughput protein-interaction data.
Gentleman R, Huber W.
Genome Biol. 2007;8(10):112. Review.
Related citations
Molecular and cellular approaches for the detection of protein-protein interactions: latest techniques and current limitations.
Lalonde S, Ehrhardt DW, Loqué D, Chen J, Rhee SY, Frommer WB.
Plant J. 2008 Feb;53(4):610-35. Review.
A probabilistic framework to predict protein function from interaction data integrated with semantic knowledge.
Cho YR, Shi L, Ramanathan M, Zhang A.
BMC Bioinformatics. 2008 Sep 18;9:382.
Literature-curated protein interaction datasets.
Cusick ME, Yu H, Smolyar A, Venkatesan K, Carvunis AR, Simonis N, Rual JF, Borick H, Braun P, Dreze M, Vandenhaute J, Galli M, Yazaki J, Hill DE, Ecker JR, Roth FP, Vidal M.
Nat Methods. 2009 Jan;6(1):39-46.
Probabilistic modeling of systematic errors in two-hybrid experiments.
Sontag D, Singh R, Berger B.
Pac Symp Biocomput. 2007:445-57.
Predicting co-complexed protein pairs from heterogeneous data.
Qiu J, Noble WS.
PLoS Comput Biol. 2008 Apr 18;4(4):e1000054.
Inferring protein-protein interaction networks from protein complex data.
Martin S, Mao Z, Chan LS, Rasheed S.
Int J Bioinform Res Appl. 2007;3(4):480-92.
ProtQuant: a tool for the label-free quantification of MudPIT proteomics data.
Bridges SM, Magee GB, Wang N, Williams WP, Burgess SC, Nanduri B.
BMC Bioinformatics. 2007 Nov 1;8 Suppl 7:S24.
Influence of protein abundance on high-throughput protein-protein interaction detection.
Ivanic J, Yu X, Wallqvist A, Reifman J.
PLoS One. 2009 Jun 5;4(6):e5815.
Integrating statistical predictions and experimental verifications for enhancing protein-chemical interaction predictions in virtual screening.
Nagamine N, Shirakawa T, Minato Y, Torii K, Kobayashi H, Imoto M, Sakakibara Y.
PLoS Comput Biol. 2009 Jun;5(6):e1000397. Epub 2009 Jun 5.
Precision and recall estimates for two-hybrid screens.
Huang H, Bader JS.
Bioinformatics. 2009 Feb 1;25(3):372-8. Epub 2008 Dec 17.
Properties of average score distributions of SEQUEST: the probability ratio method.
Martínez-Bartolomé S, Navarro P, Martín-Maroto F, López-Ferrer D, Ramos-Fernández A, Villar M, García-Ruiz JP, Vázquez J.
Mol Cell Proteomics. 2008 Jun;7(6):1135-45. Epub 2008 Feb 25.
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;5(8):e1000490. Epub 2009 Aug 28.
A surface display yeast two-hybrid screening system for high-throughput protein interactome mapping.
Chen J, Zhou J, Sanders CK, Nolan JP, Cai H.
Anal Biochem. 2009 Jul 1;390(1):29-37. Epub 2009 Mar 17.
Interaction trap/two-hybrid system to identify interacting proteins.
Golemis EA, Serebriiskii I, Finley RL Jr, Kolonin MG, Gyuris J, Brent R.
Curr Protoc Protein Sci. 2009 Aug;Chapter 19:Unit19.2.
Filtering strategies for improving protein identification in high-throughput MS/MS studies.
Salmi J, Nyman TA, Nevalainen OS, Aittokallio T.
Proteomics. 2009 Feb;9(4):848-60. Review.
From pull-down data to protein interaction networks and complexes with biological relevance.
Zhang B, Park BH, Karpinets T, Samatova NF.
Bioinformatics. 2008 Apr 1;24(7):979-86. Epub 2008 Feb 26.
Interactive three-dimensional visualization and contextual analysis of protein interaction networks.
Ho E, Webber R, Wilkins MR.
J Proteome Res. 2008 Jan;7(1):104-12. Epub 2007 Nov 20.
Improving domain-based protein interaction prediction using biologically significant negative datasets.
Li XL, Tan SH, Ng SK.
Int J Data Min Bioinform. 2006;1(2):138-49.
Curr Protoc Protein Sci. 2001 May;Chapter 19:Unit19.2.
Filter your results:
Your browsing activity is empty.
Activity recording is turned off.
Turn recording back on