Computationally predicting protein-RNA interactions using only positive and unlabeled examples

Journal of Bioinformatics and Computational Biology

Volumn 13, Issue 3, 2015, Pages

  Cheng, Zhanzhan ^a   Zhou, Shuigeng ^a   Guan, Jihong ^b  

^a FUDAN UNIVERSITY   (China)

^b TONGJI UNIVERSITY   (China)

Author keywords

biased SVM; prediction; Protein RNA interactions

Indexed keywords

BONE PROSTHESIS; HYDROXYAPATITE; PROTEIN; RNA;

ANIMAL; BONE PROSTHESIS; CAENORHABDITIS ELEGANS; CHEMISTRY; DROSOPHILA MELANOGASTER; ESCHERICHIA COLI; GENETICS; HUMAN; METABOLISM; MOUSE; PROCEDURES; PROTEIN ANALYSIS; PROTEIN DATABASE; SACCHAROMYCES CEREVISIAE; SUPPORT VECTOR MACHINE;

ANIMALS; BONE SUBSTITUTES; CAENORHABDITIS ELEGANS; DATABASES, PROTEIN; DROSOPHILA MELANOGASTER; ESCHERICHIA COLI; HUMANS; MICE; PROTEIN INTERACTION MAPPING; PROTEINS; RNA; SACCHAROMYCES CEREVISIAE; SUPPORT VECTOR MACHINE;

EID: 84929516625     PISSN: 02197200     EISSN: 17576334     Source Type: Journal    
DOI: 10.1142/S021972001541005X     Document Type: Conference Paper

References (38)

1. Moore PB, The three-dimensional structure of the ribosome and its components, Annu Rev Biophys Biomol Struct 27(1):35-58, 1998.
2. Moras D, Structural and functional relationships between aminoacyl-tRNA synthetases, Trends Biochem Sci 17(4):159-164, 1992.
3. Ramakrishnan V, White SW, Ribosomal protein structures: Insights into the architecture, machinery and evolution of the ribosome, Trends Biochem Sci 23(6):208-212, 1998.
4. Mata J, Marguerat S, B ähler J, Post-transcriptional control of gene expression: A genome-wide perspective, Trends Biochem Sci 30(9):506-514, 2005.
5. Siomi H, Dreyfuss G, RNA-binding proteins as regulators of gene expression, Curr Opin Genet Dev 7(3):345-353, 1997.
6. Frank DN, Pace NR, Ribonuclease P: Unity and diversity in a tRNA processing ribozyme, Annu Rev Biochem 67(1):153-180, 1998.
7. Ramos A, Va rani G, A new method to detect long-range protein-RNA contacts: NMR detection of electron-proton relaxation induced by nitroxide spin-labeled RNA, J Am Chem Soc 120(42):10992-10993, 1998.
8. Singh D, Febbo PG, Ross K, Jackson DG, Manola J, Ladd C, Tamayo P, Renshaw AA, D'Amico AV, Richie JP et al., Gene expression correlates of clinical prostate cancer behavior, Cancer Cell 1(2):203-209, 2002.
9. Hall KB, RNA-protein interactions, Curr Opin Struct Biol 12(3):283-288, 2002.
10. Tian B, Bevilacqua PC, Diegelman-Parente A, Mathews MB, The double-stranded-RNAbinding motif: Interference and much more, Nat Rev Mol Cell Biol 5(12):1013-1023, 2004.
11. Wang Y, Chen X, Liu ZP, Huang Q, Wang Y, Xu D, Zhang XS, Chen R, Chen L , De novo prediction of RNA-protein interactions from sequence information, Mol Biosyst 9(1):133- 142, 2013.
12. Barkan A, Genome-wide analysis of RNA-protein interactions in plants, in Plant Systems Biology, Springer, pp. 13-37, 2009.
13. Baroni TE, Chittur SV, George AD, Tenenbaum SA, Advances in RIP-chip analysis: RNA-binding protein immunoprecipitation-microarray profiling, in Po st-Transcriptional Gene Regulation, Springer, pp. 93-108, 2008.
14. Charon C, Moreno AB, Bardou F, Crespi M, Non-protein-coding RNAs and their interacting RNA-binding proteins in the plant cell nucleus, Mol Plant 3(4):729 -739, 2010.
15. Kaymak E, Wee L, Ryder SP, Structure and function of nematode RNA-binding proteins, Curr Opin Struct Biol 20(3):305 -312, 2010.
16. Kim MY, Hur J, Jeong S, Emerging roles of RNA and RNA-binding protein network in cancer cells, BMB Rep 42(3):125-130, 2009.
17. Pacheco A, Martinez-Salas E, Insights into the biology of IRES elements through riboproteomic approaches, J Biomed Biotechnol 2010:458927, 2010.
18. Jones S, Daley DT, Luscombe NM, Berman HM, Thornton JM, Protein-RNA interactions: A structural analysis, Nucl Acids Res 29(4):943-954, 2001.
19. Ellis JJ, Broom M, Jones S, Protein-RNA interactions: Structural analysis and functional classes, Proteins 66(4):903-911, 2007.
20. Auweter SD, Oberstrass FC, Allain FHT, Sequence-specific binding of single-stranded RNA: Is there a code for recognition? Nucl Acids Res 34(17):4943-4959, 2006.
21. Hermann T,Westhof E, Simulations of the dynamics at an RNA-protein interface, Nat Struct Mol Biol, 6(6),540-544, 1999.
22. Pancaldi V, Bä hler J, In silico characterization and prediction of global protein-mRNA interactions in yeast, Nucl Acids Res 39(14):5826- 5836, 2011.
23. Muppirala UK, Honavar V G, Dobbs D, Predicting RNA-protein interactions using only sequence information, BMC Bioinformatics 12(1):489, 2011.
24. Li X, Liu B, Learning to classify texts using positive and unlabeled data, IJCAI, pp. 587-592, 2003.
25. Liu B, Lee WS, Yu PS, Li X, Partially supervised classification of text documents, ICML, Citeseer, pp. 387-394, 2002.
26. Mordelet F, Vert JP, ProDiGe: Prioritization of disease genes with multitask machine learning from positive and unlabeled examples, BMC Bioinformatics 12(1):389, 2011.
27. Yang P, Li X, Chua HN, Kwoh C K, Ng SK, Ensemble positive unlabeled learning for disease gene identification, PLoS One 9(5):e97079, 2014, doi: 10.1371/journal. pone.0097079.
28. Yang P, Li XL, Mei JP, Kwoh CK, Ng SK, Positive-unlabeled learning for disease gene identification, Bioinformatics, 2012, doi: 10.1093/bioinformatics/bts504.
29. Lewis BA, W alia RR, Terribilini M, Ferguson J, Zheng C, Honavar V, Dobbs D, PRIDB: A protein-RNA interface database, Nucl Acids Res 39(suppl 1):D277-D282, 2011.
30. Wu T, Wang J, Liu C, Zhan g Y, Shi B, Zhu X, Zhang Z, Skogerbø G, Chen L, Lu H et al., NPInter: the noncoding RNAs and protein related biomacromolecules interaction database, Nucl Acids Res 34(suppl 1):D150-D152, 2006.
31. Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat T, Weissig H, Shindyalov IN, Bourne PE, The protein data bank, Nucl Acids Res 28(1):235-242, 2000.
32. Han L, Cai C, Ji Z, Cao Z, Cui J, Chen Y, Predicting functional family of novel enzymes irrespective of sequence similarity: A statistical learning approach, Nucl Acids Res 32 (21):6437-6444, 2004.
33. Liu ZP, Wu LY, Wang Y, Zhang XS, Chen L, Prediction of protein-RNA binding sites by a random forest method with combined features, Bioinformatics 26(13):1616 -1622, 2010.
34. Terribilini M, Lee JH, Yan C, Jernigan RL, Honavar V, Dobbs D, Prediction of RNA binding sites in proteins from amino acid sequence, RNA 12(8):1450-1462, 2006.
35. Shen J, Zhang J, Luo X, Zhu W, Yu K, Chen K, Li Y, Jiang H, Predicting protein-protein interactions based only on sequences information, Proc Natl Acad Sci 104(11):4337-4341, 2007.
36. Liu B, Dai Y, Li X, Lee WS, Yu PS, Building text classifiers using positive and unlabeled examples, Third IEEE Int Conf, Data Mining, 2003, ICDM 2003, IEEE, pp. 179-186, 2003.
37. Joachims T, Making large-scale svm learning practical, in Support Vector Learning, Schölkopf B, Burges C, Smola A (eds.), MIT-Press, 1999, pp. 169-184.
38. Bengio Y, Learning deep architectures for AI, Found Trends Mach Learn 2(1):1-127, 2009.