Prediction of microRNA-disease associations based on social network analysis methods

BioMed Research International

Volumn 2015, Issue , 2015, Pages

  Zou, Quan ^a,b   Li, Jinjin ^a   Hong, Qingqi ^a   Lin, Ziyu ^a   Wu, Yun ^c   Shi, Hua ^c   Ju, Ying ^a  

^a XIAMEN UNIVERSITY   (China)

^b TIANJIN UNIVERSITY   (China)

^c XIAMEN UNIVERSITY OF TECHNOLOGY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

MICRORNA;

ALGORITHM; ARTICLE; DATA BASE; DISEASE ASSOCIATION; HUMAN; MACHINE LEARNING; PHENOTYPE; PREDICTION; SOCIAL NETWORK; SUPPORT VECTOR MACHINE; AUTOMATED PATTERN RECOGNITION; BIOLOGICAL MODEL; COMPUTER SIMULATION; GENETIC DATABASE; GENETIC PREDISPOSITION; GENETICS; PROCEDURES; SIGNAL TRANSDUCTION;

ALGORITHMS; COMPUTER SIMULATION; DATABASES, GENETIC; GENETIC PREDISPOSITION TO DISEASE; HUMANS; MACHINE LEARNING; MICRORNAS; MODELS, GENETIC; PATTERN RECOGNITION, AUTOMATED; SIGNAL TRANSDUCTION; SOCIAL NETWORKING;

EID: 84939197918     PISSN: 23146133     EISSN: 23146141     Source Type: Journal    
DOI: 10.1155/2015/810514     Document Type: Article

References (62)

1. P. Jimenez, F. Thomas, and C. Torras, "3D collision detection: A survey," Computers and Graphics, vol. 25, no. 2, pp. 269-285, 2001.
2. T. Uziel, F. V. Karginov, S. Xie et al., "The miR-17∼92 cluster collaborates with the Sonic Hedgehog pathway in medulloblastoma," Proceedings of the National Academy of Sciences of the United States of America, vol. 106, no. 8, pp. 2812-2817, 2009.
3. H. Ding, P. Feng, W. Chen, and H. Lin, "Identification of bacteriophage virion proteins by the ANOVA feature selection and analysis," Molecular BioSystems, vol. 10, no. 8, pp. 2229-2235, 2014.
4. Q. Cui, Z. Yu, E. O. Purisima, and E. Wang, "Principles of microRNA regulation of a human cellular signaling network," Molecular Systems Biology, vol. 2, article 46, 2006.
5. D. Wang, J. Wang, M. Lu, F. Song, and Q. Cui, "Inferring the human microRNA functional similarity and functional network based on microRNA-associated diseases," Bioinformatics, vol. 26, no. 13, pp. 1644-1650, 2010.
6. Y. Wang, T. Cui, C. Zhang et al., "Global protein-protein interaction network in the human pathogen mycobacterium tuberculosis H37Rv," Journal of Proteome Research, vol. 9, no. 12, pp. 6665-6677, 2010.
7. Y. Wang, L. Chen, B. Chen et al., "Mammalian ncRNA-disease repository: a global view of ncRNA-mediated disease network," Cell Death and Disease, vol. 4, article e765, 2013.
8. A. Esquela-Kerscher and F. J. Slack, "Oncomirs-microRNAs with a role in cancer," Nature Reviews Cancer, vol. 6, no. 4, pp. 259-269, 2006.
9. M. V. G. Latronico, D. Catalucci, and G. Condorelli, "Emerging role of microRNAs in cardiovascular biology," Circulation Research, vol. 101, no. 12, pp. 1225-1236, 2007.
10. M. Lu, Q. Zhang, M. Deng et al., "An analysis of human microRNA and disease associations," PLoS ONE, vol. 3, no. 10, Article ID e3420, 2008.
11. G. A. Calin and C. M. Croce, "MicroRNA signatures in human cancers," Nature Reviews Cancer, vol. 6, no. 11, pp. 857-866, 2006.
12. M. V. Iorio, M. Ferracin, C.-G. Liu et al., "MicroRNA gene expression deregulation in human breast cancer," Cancer Research, vol. 65, no. 16, pp. 7065-7070, 2005.
13. A. Esquela-Kerscher, P. Trang, J. F. Wiggins et al., "The let microRNA reduces tumor growth in mouse models of lung cancer," Cell Cycle, vol. 7, no. 6, pp. 759-764, 2008.
14. Q. Wang, L. Wei, X. Guan, Y. Wu, Q. Zou, and Z. Ji, "Briefing in family characteristics of microRNAs and their applications in cancer research," Biochimica et Biophysica Acta-Proteins and Proteomics, vol. 1844, no. 1, pp. 191-197, 2014.
15. B. Yang, H. Lin, J. Xiao et al., "The muscle-specific microRNA miR-1 regulates cardiac arrhythmogenic potential by targeting GJA1 and KCNJ2," Nature Medicine, vol. 13, no. 4, pp. 486-491, 2007.
16. R. W. Chen, L. T. Bemis, C. M. Amato et al., "Truncation in CCND1 mRNA alters miR-16-1 regulation in mantle cell lymphoma," Blood, vol. 112, no. 3, pp. 822-829, 2008.
17. J. Xu, C.-X. Li, Y.-S. Li et al., "MiRNA-miRNA synergistic network: construction via co-regulating functional modules and disease miRNA topological features," Nucleic Acids Research, vol. 39, no. 3, pp. 825-836, 2011.
18. T.-H. Cheung, K.-N. M. Man, M.-Y. Yu et al., "Dysregulated microRNAs in the pathogenesis and progression of cervical neoplasm," Cell Cycle, vol. 11, no. 15, pp. 2876-2884, 2012.
19. K. Han, P. Xuan, J. Ding, Z. J. Zhao, L. Hui, and Y. L. Zhong, "Prediction of disease-related microRNAs by incorporating functional similarity and common association information," Genetics and Molecular Research, vol. 13, no. 1, pp. 2009-2019, 2014.
20. T. Huang and Y.-D. Cai, "An information-theoretic machine learning approach to expression QTL analysis," PLoS ONE, vol. 8, no. 6, Article ID e67899, 2013.
21. Q. Zou, X. Li, W. Jiang, Z. Lin, G. Li, and K. Chen, "Survey of MapReduce frame operation in bioinformatics," Briefings in Bioinformatics, vol. 15, no. 4, pp. 637-647, 2014.
22. Q. Zou, J. Li, C. Wang, and X. Zeng, "Approaches for recognizing disease genes based on network," BioMed Research International, vol. 2014, Article ID 416323, 10 pages, 2014.
23. G. Yu, C.-L. Xiao, X. Bo et al., "A new method for measuring functional similarity of microRNAs," Journal of Integrated OMICS, vol. 1, no. 1, pp. 49-54, 2010.
24. B. Liu, J. Xu, S. Fan, R. Xu, J. Zhou, and X. Wang, "PseDNAPro: DNA-binding protein identification by combining Chous PseAAC and physicochemical distance transformation," Molecular Informatics, vol. 34, no. 1, pp. 8-17, 2015.
25. B. Liu, X. Wang, Q. Zou, Q. Dong, and Q. Chen, "Protein remote homology detection by combining chous pseudo amino acid composition and profile-based protein representation," Molecular Informatics, vol. 32, no. 9-10, pp. 775-782, 2013.
26. Z. Du, L. Li, C.-F. Chen, P. S. Yu, and J. Z. Wang, "G-SESAME: web tools for GO-term-based gene similarity analysis and knowledge discovery," Nucleic Acids Research, vol. 37, no. 2, pp. W345-W349, 2009.
27. S. G. Lee, J. U. Hur, and Y. S. Kim, "A graph-theoretic modeling on GO space for biological interpretation of gene clusters," Bioinformatics, vol. 20, no. 3, pp. 381-388, 2004.
28. K. Li, D. Wu, X. Chen et al., "Current and emerging biomarkers of cell death in human disease," BioMed Research International, vol. 2014, Article ID690103, 10 pages, 2014.
29. J. Lin, C. M. Gan, X. Zhang et al., "A multidimensional analysis of genes mutated in breast and colorectal cancers," Genome Research, vol. 17, no. 9, pp. 1304-1318, 2007.
30. P. W. Lord, R. D. Stevens, A. Brass, and C. A. Goble, "Investigating semantic similarity measures across the gene ontology: the relationship between sequence and annotation," Bioinformatics, vol. 19, no. 10, pp. 1275-1283, 2003.
31. C. Pesquita, D. Faria, H. Bastos, A. E. N. Ferreira, A. O. Falcao, and F. M. Couto, "Metrics for GO based protein semantic similarity: a systematic evaluation," BMC Bioinformatics, vol. 9, article S4, 2008.
32. J. Z. Wang, Z. Du, R. Payattakool, P. S. Yu, and C.-F. Chen, "A new method to measure the semantic similarity of GO terms," Bioinformatics, vol. 23, no. 10, pp. 1274-1281, 2007.
33. W. Li, E. Deng, H. Ding, W. Chen, and H. Lin, "iORI-PseKNC: a predictor for identifying origin of replication with pseudo k-tuple nucleotide composition," Chemometrics and Intelligent Laboratory Systems, vol. 141, pp. 100-106, 2015.
34. Y. Li, L. Zhuang, Y. Wang et al., "Connect the dots: a systems level approach for analyzing the miRNA-mediated cell death network," Autophagy, vol. 9, no. 3, pp. 436-439, 2013.
35. Q. Jiang, Y. Wang, Y. Hao et al., "miR2Disease: a manually curated database for microRNA deregulation in human disease," Nucleic Acids Research, vol. 37, no. 1, pp. D98-D104, 2009.
36. U. M. Singh-Blom, N. Natarajan, A. Tewari, J. O. Woods, I. S. Dhillon, and E. M. Marcotte, "Prediction and validation of gene-disease associations using methods inspired by social network analyses," PLoS ONE, vol. 8, no. 5, Article ID e58977, 2013.
37. B. Grisart, W. Coppieters, F. Farnir et al., "Positional candidate cloning of a QTL in dairy cattle: identification of a missense mutation in the bovine DGAT1 gene with major effect on milk yield and composition," Genome Research, vol. 12, no. 2, pp. 222-231, 2002.
38. A. M. Krichevsky, K. S. King, C. P. Donahue, K. Khrapko, and K. S. Kosik, "A microRNA array reveals extensive regulation of microRNAs during brain development," RNA, vol. 9, no. 10, pp. 1274-1281, 2003.
39. G. Thaller, C. Kuhn, A. Winter et al., "DGAT1, a new positional and functional candidate gene for intramuscular fat deposition in cattle," Animal Genetics, vol. 34, no. 5, pp. 354-357, 2003.
40. L. Cheng, Z.-G. Hou, Y. Lin, M. Tan, W. C. Zhang, and F.-X. Wu, "Recurrent neural network for non-smooth convex optimization problems with application to the identification of genetic regulatory networks," IEEE Transactions on Neural Networks, vol. 22, no. 5, pp. 714-726, 2011.
41. A. Clop, F. Marcq, H. Takeda et al., "A mutation creating a potential illegitimate microRNA target site in the myostatin gene affects muscularity in sheep," Nature Genetics, vol. 38, no. 7, pp. 813-818, 2006.
42. J. Lim, T. Hao, C. Shaw et al., "A protein-protein interaction network for human inherited ataxias and disorders of Purkinje cell degeneration," Cell, vol. 125, no. 4, pp. 801-814, 2006.
43. H. Lin, E. Deng, H. Ding, W. Chen, and K. Chou, "iPro54- PseKNC: a sequence-based predictor for identifying sigma promoters in prokaryote with pseudo k-tuple nucleotide composition," Nucleic Acids Research, vol. 42, no. 21, pp. 12961-12972, 2014.
44. M. Oti and H. G. Brunner, "The modular nature of genetic diseases," Clinical Genetics, vol. 71, no. 1, pp. 1-11, 2007.
45. L. D. Wood, D. W. Parsons, S. Jones et al., "The genomic landscapes of human breast and colorectal cancers," Science, vol. 318, no. 5853, pp. 1108-1113, 2007.
46. D. Mrozek, B. Maysiak-Mrozek, and A. Sinik, "SearchGenBank: interactive orchestration and ad-hoc choreography of Web services in the exploration of the biomedical resources of the National Center For Biotechnology Information," BMC Bioinformatics, vol. 14, article 73, 9 pages, 2013.
47. B. Liu, J. Xu, Q. Zou, R. Xu, X. Wang, and Q. Chen, "Using distances between Top-n-gram and residue pairs for protein remote homology detection," BMC Bioinformatics, vol. 15, supplement 2, article S3, pp. 133-139, 2014.
48. J.-B. Pan, S.-C. Hu, H. Wang, Q. Zou, and Z.-L. Ji, "PaGeFinder: quantitative identification of spatiotemporal pattern genes," Bioinformatics, vol. 28, no. 11, pp. 1544-1545, 2012.
49. L. Wei, M. Liao, Y. Gao, R. Ji, Z. He, and Q. Zou, "Improved and promising identification of human microRNAs by incorporating a high-quality negative set," IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 11, no. 1, pp. 192-201, 2014.
50. Z. G. Hou, L. Cheng, M. Tan, and X. Wang, "Distributed adaptive coordinated control of multi-manipulator systems using neural networks," in Robot Intelligence, pp. 49-69, Springer, London, UK, 2010.
51. B. Liu, X. Wang, Q. Chen, Q. Dong, and X. Lan, "Using amino acid physicochemical distance transformation for fast protein remote homology detection," PLoS ONE, vol. 7, no. 9, Article ID e46633, 2012.
52. M. A. van Driel, J. Bruggeman, G. Vriend, H. G. Brunner, and J. A. M. Leunissen, "A text-mining analysis of the human phenome," European Journal of Human Genetics, vol. 14, no. 5, pp. 535-542, 2006.
53. A. Hamosh, A. F. Scott, J. S. Amberger, C. A. Bocchini, and V. A. McKusick, "Online Mendelian Inheritance in Man (OMIM), a knowledgebase of human genes and genetic disorders," Nucleic Acids Research, vol. 33, no. supplement 1, pp. D514-D517, 2005.
54. U. Ala, R. M. Piro, E. Grassi et al., "Prediction of human disease genes by human-mouse conserved coexpression analysis," PLoS Computational Biology, vol. 4, no. 3, Article ID e1000043, 2008.
55. H. Chen and Z. Zhang, "Similarity-based methods for potential human microRNA-disease association prediction," BMC Medical Genomics, vol. 6, article 12, pp. 215-221, 2013.
56. Q. Jiang, Y. Hao, G. Wang et al., "Prioritization of disease microRNAs through a human phenome-microRNAome network," BMC Systems Biology, vol. 4, article S2, 2010.
57. L. Katz, "A new status index derived fromsociometric analysis," Psychometrika, vol. 18, no. 1, pp. 39-43, 1953.
58. Y. Li and J. C. Patra, "Genome-wide inferring gene-phenotype relationship by walking on the heterogeneous network," Bioinformatics, vol. 26, no. 9, Article IDbtq108, pp. 1219-1224, 2010.
59. O. Vanunu, O. Magger, E. Ruppin, T. Shlomi, and R. Sharan, "Associating genes and protein complexes with disease via network propagation," PLoS Computational Biology, vol. 6, no. 1, Article ID 1000641, 2010.
60. X. Wu, R. Jiang, M. Q. Zhang, and S. Li, "Network-based global inference of human disease genes," Molecular Systems Biology, vol. 4, article 189, 2008.
61. F. Mordelet and J.-P. Vert, "A bagging SVM to learn from positive and unlabeled examples," Pattern Recognition Letters, vol. 37, no. 1, pp. 201-209, 2014.
62. H. Chen and Z. Zhang, "Prediction of associations between OMIM diseases and MicroRNAs by random walk on OMIM disease similarity network," The Scientific World Journal, vol. 2013, Article ID 204658, 6 pages, 2013.