Protein interaction predictions from diverse sources

Drug Discovery Today

Volumn 13, Issue 9-10, 2008, Pages 409-416

  Liu, Yin ^a   Kim, Inyoung ^b   Zhao, Hongyu ^c  

^a UNIVERSITY OF TEXAS MEDICAL SCHOOL   (United States)

^b VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY   (United States)

^c YALE UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

PROTEIN; PROTEOME;

ACCURACY; ALGORITHM; AMINO ACID SEQUENCE; ANALYTICAL ERROR; BAYES THEOREM; BIOINFORMATICS; DRUG TARGETING; FUNCTIONAL GENOMICS; GENOMICS; GOLD STANDARD; HIGH THROUGHPUT SCREENING; HUMAN; MAXIMUM LIKELIHOOD METHOD; METHODOLOGY; NONHUMAN; PARSIMONY ANALYSIS; PROTEIN DOMAIN; PROTEIN FUNCTION; PROTEIN PROTEIN INTERACTION; PROTEIN STRUCTURE; PROTEOMICS; REVIEW; TWO HYBRID SYSTEM;

ANIMALS; COMPUTATIONAL BIOLOGY; HUMANS; PROTEIN INTERACTION MAPPING;

EID: 43049159751     PISSN: 13596446     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.drudis.2008.01.005     Document Type: Review

References (64)

1. Arkin M., and Wells J. Small-molecule inhibitors of protein-protein interactions: progressing towards the dream. Nat. Rev. Drug Discov. 3 (2004) 301-317
2. Uetz P., et al. A comprehensive analysis of protein-protein interactions in Saccharomyces cerevisiae. Nature 403 (2000) 623-627
3. Ito T., et al. A comprehensive two-hybrid analysis to explore the yeast protein interactome. Proc. Natl. Acad. Sci. U.S.A. 98 (2001) 4569-4574
4. Giot L., et al. A protein interaction map of Drosophila melanogaster. Science 302 (2003) 1727-1736
5. Li S., et al. A map of the interactome network of the metazoan C. elegans. Science 303 (2004) 540-543
6. Rual J.F., et al. Towards a proteome-scale map of the human protein-protein interaction network. Nature 437 (2005) 1173-1178
7. LaCount D.J., et al. A protein interaction network of the malaria parasite plasmodium falciparum. Nature 438 (2005) 103-107
8. Von Mering C., et al. Comparative assessment of large-scale data sets of protein-protein interactions. Nature 417 (2002) 399-403
9. Hart G.T., et al. How complete are current yeast and human protein-interaction networks?. Genome Biol. 7 (2006) 120
10. Scholtens D., et al. Estimating node degree in bait-prey graphs. Bioinformatics 24 (2008) 218-224
11. Huang H., et al. Where have all the interactions gone? Estimating the coverage of two-hybrid protein interaction maps. PLoS Comput. Biol. 3 (2007) e214
12. Marcotte E.M., et al. Detecting protein function and protein-protein interactions from genome sequence. Science 285 (1999) 751-753
13. Enright A.J., et al. Protein interaction maps for complete genomes based on gene fusion events. Nature 402 (1999) 86-90
14. Goh C.S., and Cohen F.E. Co-evolutionary analysis reveals insights into protein-protein interactions. J. Mol. Biol. 324 (2002) 177-192
15. Pazos F., et al. Assessing protein co-evolution in the context of the tree of life assists in the prediction of the interactome. J. Mol. Biol. 352 (2003) 1002-1015
16. Matthews L.R., et al. Identification of potential interaction networks using sequence-based searches for conserved protein-protein interactions or 'interologs'. Genome Res. 11 (2001) 2120-2126
17. Dandekar T., et al. Conservation of gene order: a finger print of proteins that physically interact. Trend Biochem. Sci. 23 (1998) 324-328
18. Overbeek R., et al. The use of gene clusters to infer functional coupling. Proc. Natl. Acad. U.S.A. 96 (1999) 2896-2901
19. Jansen R., et al. Relating whole-genome expression data with protein-protein interaction. Genome Res. 12 (2002) 37-46
20. Ge H., et al. Correlation between transcriptome and interactome mapping data from Saccaromyces cerevisiae. Nat. Genet. 29 (2001) 482-486
21. Comeau S., et al. ClusPro: an automated docking and discrimination method for the prediction of protein complexes. Bioinformatics 20 (2004) 45-50
22. Sprinzak E., and Margalit H. Corrlated sequence-signatures as markers of protein-protein interaction. J. Mol. Biol. 311 (2001) 681-692
23. Deng M., et al. Inferring domain-domain interactions from protein-protein interactions. Genome Res. 12 (2002) 1540-1548
24. Gomez S.M., et al. Learning to predict protein-protein interactions from protein sequences. Bioinformatics 19 (2003) 1875-1881
25. Shi T., et al. Computational methods for protein-protein interaction and their application. Curr. Protein Pept. Sci. 6 (2005) 443-449
26. Shoemaker B.A., and Panchenko A.R. Deciphering protein-protein interactions. Part II. Computational methods to predict protein and domain interaction partners. PloS Comput. Biol. 3 (2007) e43
27. Bonvin A.M. Flexible protein-protein docking. Curr. Opin. Struct. Biol. 16 (2006) 194-200
28. Shoemaker B.A., and Panchenko A.R. Deciphering protein-protein interactions. Part I. Experimental techniques and databases. PloS Comput. Biol. 3 (2007) e42
29. Chiang T., et al. Coverage and error models of protein-protein interaction data by directed graph analysis. Genome Biol. 8 (2007) R186
30. Liu Y., et al. Inferring protein-protein interactions through high-throughput interaction data from diverse organisms. Bioinformatics 21 (2005) 3279-3285
31. Kim I., et al. Bayesian methods for predicting interacting protein pairs using domain information. Biometrics 63 (2007) 824-833
32. Riley R., et al. Inferring protein domain interactions from databases of interacting proteins. Genome Biol. 6 (2005) R89
33. Salwinski L., et al. The database of interacting proteins: 2004 update. Nucleic Acids Res. 32 (2004) D449-D451
34. Guimaraes K.S., et al. Predicting domain-domain interactions using a parsimony approach. Genome Biol. 7 (2006) R104
35. Finn R.D., et al. Pfam: clans, web tools and services. Nucleic Acids Res. 34 (2006) D247-D251
36. Martin S., et al. Predicting protein-protein interactions using signature products. Bioinformatics 21 (2005) 218-226
37. Goldberg D.S., and Roth F.P. Assessing experimentally derived interactions in a small world. Proc. Natl. Acad. Sci. U.S.A. 100 (2003) 4372-4376
38. Qi Y., et al. Evaluation of different biological data and computational classification methods for use in protein interaction prediction. Proteins: Struct., Funct. Bioinform. 63 (2006) 490-500
39. Deane C.M., et al. Protein interactions: two methods for assessment of the reliability of high throughput observations. Mol Cell Proteomics 1 (2002) 349-356
40. Jansen R., et al. A Bayesian networks approach for predicting protein-protein interactions from genomic data. Science 302 (2003) 449-453
41. Lin N., et al. Information assessment on prediction protein-protein interactions. BMC Bioinform. 5 (2004) 154
42. Lu L.J., et al. Assessing the limits of genomic data integration for predicting protein networks. Genome Res. 15 (2005) 945-953
43. Yu H., et al. Genomic analysis of gene expression relationships in transcriptional regulatory networks. Trends Genet. 19 (2003) 422-427
44. Bader J.S., et al. Gaining confidence in high-throughput protein interaction networks. Nat. Biotechnol. 22 (2004) 78-85
45. Sharan R., et al. Conserved patterns of protein interaction in multiple species. Proc. Natl. Acad. Sci. U.S.A. 102 (2005) 1974-1979
46. Ben-Hur A., and Noble W.S. Kernel methods for predicting protein-protein interactions. Bioinformatics 20 (2005) 3346-3352
47. Lee I., et al. A probabilistic functional network of yeast genes. Science 302 (2004) 1555-1558
48. Stolovitzky G., et al. Dialogue on reverse-engineering assessment and methods: the DREAM of high-throughput pathway inference. Ann. N. Y. Acad. Sci. 1115 (2007) 1-22
49. Mewes M., et al. MIPS: analysis and annotation of proteins from whole genomes in 2005. Nucleic Acids Res. 34 (2006) D169-D172
50. Suthram S., et al. A direct comparison of protein interaction confidence assignment schemes. BMC Bioinform. 7 (2006) 360
51. Davis J., and Goadrich M. The relationship between precision-recall and ROC curves. Proceedings of the 23rd International Conference on Machine Learning. Pittsburgh, PA (2007) 233-240
52. Strobl C., et al. Bias in random forest variable importance measures: Illustrations, sources and a solution. BMC Bioinform. 8 (2007) 25
53. Rajagopala S., et al. The protein network of bacterial motility. Mol. Syst. Biol. 3 (2007) 128
54. Barabasi A.L., and Oltvai Z.N. Network biology: understanding the cell's functional organization. Nat. Rev. Genet. 5 (2004) 101-113
55. Gavin A.C., et al. Proteome survey reveals modularity of the yeast cell machinery. Nature 440 (2006) 631-636
56. Krogan N.J., et al. Global landscape of protein complexes in the yeast Saccharomyces cerevisiae. Nature 440 (2006) 637-643
57. Demeter J., et al. The Stanford microarray database: implementation of new analysis tools and open source release of software. Nucleic Acids Res. 35 (2007) D766-D770
58. Gene Ontology Consortim. (2006) The gene ontology (GO) project in 2006. Nucleic Acids Res. 34, D322-326
59. Ghaemmaghami S., et al. Global analysis of protein expression in yeast. Nature 425 (2003) 737-741
60. Tong A.H.Y., et al. Global mapping of the yeast genetic interaction network. Science 303 (2004) 808-813
61. Harbison C.T., et al. Transcriptional regulatory code of a eukaryotic genome. Nature 431 (2004) 99-104
62. Sprinzak E., et al. Characterization and prediction of protein-protein interactions within and between complexes. Proc. Natl. Acad. Sci. U.S.A. 103 (2005) 14718-14723
63. Zhang L., et al. Predicting co-complexes protein pairs using genomic and proteomic data integration. BMC Bioinform. 5 (2004) 38
64. Lee H., et al. An integrated approach to the prediction of domain-domain interactions. BMC Bioinform. 7 (2006) 269