FMLNCSIM: Fuzzy measure-based lncRNA functional similarity calculation model

Oncotarget

Volumn 7, Issue 29, 2016, Pages 45948-45958

  Chen, Xing ^a   Huang, Yu An ^b   Wang, Xue Song ^a   You, Zhu Hong ^a   Chan, Keith C C ^b  

^a CHINA UNIVERSITY OF MINING AND TECHNOLOGY   (China)

^b HONG KONG POLYTECHNIC UNIVERSITY   (Hong Kong)

Author keywords

Directed acyclic graph; Disease; Functional similarity; Fuzzy measure; lncRNAs

Indexed keywords

LONG UNTRANSLATED RNA; UCA1 PROTEIN; UNCLASSIFIED DRUG; TRANSCRIPTOME;

ACUTE MYELOBLASTIC LEUKEMIA; AREA UNDER THE CURVE; ARTICLE; AUTOMATION; CANCER GROWTH; CANCER PROGNOSIS; CANCER SURVIVAL; CLASSIFICATION ALGORITHM; CLINICAL EFFECTIVENESS; DATA BASE; DISEASE ASSOCIATION; FEASIBILITY STUDY; FUZZY MEASURE BASED LNCRNA FUNCTIONAL SIMILARITY CALCULATION MODEL; FUZZY SYSTEM; GENE PRODUCT; HUMAN; INFORMATION; INFORMATION RETRIEVAL; INTEGRATION; LAPLACIAN REGULARIZED LEAST SQUARES FOR LNCRNA DISEASE ASSOCIATION; LUNG CANCER; MATHEMATICAL MODEL; PERFORMANCE MEASUREMENT SYSTEM; PHYSICAL ANTHROPOLOGY; PLOTS AND CURVES; PSYCHOLOGY; RELIABILITY; SIMILARITY MEASURE; TAXONOMY; TRAPEZOIDAL INTUITIONISTIC FUZZY NUMEBER; VALIDATION PROCESS; BIOLOGY; COMPUTER SIMULATION; FUZZY LOGIC; GENE EXPRESSION PROFILING; GENE REGULATORY NETWORK; GENETICS; PROCEDURES;

COMPUTATIONAL BIOLOGY; COMPUTER SIMULATION; FUZZY LOGIC; GENE EXPRESSION PROFILING; GENE REGULATORY NETWORKS; HUMANS; RNA, LONG NONCODING; TRANSCRIPTOME;

EID: 84979942197     PISSN: None     EISSN: 19492553     Source Type: Journal    
DOI: 10.18632/oncotarget.10008     Document Type: Article

References (79)

1. Kapranov P, Cheng J, Dike S, Nix DA, Duttagupta R, Willingham AT, Stadler PF, Hertel J, Hackermüller J and Hofacker IL. RNA maps reveal new RNA classes and a possible function for pervasive transcription. Science. 2007; 316:1484-1488.
2. Mercer TR, Dinger ME and Mattick JS. Long non-coding RNAs: insights into functions. Nat Rev Genet. 2009; 10:155-159.
3. Guttman M, Russell P, Ingolia NT, Weissman JS and Lander ES. Ribosome profiling provides evidence that large noncoding RNAs do not encode proteins. Cell. 2013; 154:240-251.
4. Guttman M, Garber M, Levin JZ, Donaghey J, Robinson J, Adiconis X, Fan L, Koziol MJ, Gnirke A and Nusbaum C. Ab initio reconstruction of cell type-specific transcriptomes in mouse reveals the conserved multi-exonic structure of lincRNAs. Nat Biotechnol. 2010; 28:503-510.
5. Harrow J, Frankish A, Gonzalez JM, Tapanari E, Diekhans M, Kokocinski F, Aken BL, Barrell D, Zadissa A and Searle S. GENCODE: the reference human genome annotation for The ENCODE Project. Genome Res. 2012; 22:1760-1774.
6. Ponting CP, Oliver PL and Reik W. Evolution and functions of long noncoding RNAs. Cell. 2009; 136:629-641.
7. Lander ES, Linton LM, Birren B, Nusbaum C, Zody MC, Baldwin J, Devon K, Dewar K, Doyle M and FitzHugh W. Initial sequencing and analysis of the human genome. Nature. 2001; 409:860-921.
8. Guttman M, Amit I, Garber M, French C, Lin MF, Feldser D, Huarte M, Zuk O, Carey BW, Cassady JP and Cabili MN. Chromatin signature reveals over a thousand highly conserved large non-coding RNAs in mammals. Nature. 2009; 458:223-227.
9. Wapinski O and Chang HY. Long noncoding RNAs and human disease. Trends Cell Biol. 2011; 21:354-361.
10. Wilusz JE, Sunwoo H and Spector DL. Long noncoding RNAs: functional surprises from the RNA world. Genes Dev. 2009; 23:1494-1504.
11. Amaral PP, Clark MB, Gascoigne DK, Dinger ME and Mattick JS. lncRNAdb: a reference database for long noncoding RNAs. Nucleic Acids Res. 2011; 39:D146-D151.
12. Chen G, Wang Z, Wang D, Qiu C, Liu M, Chen X, Zhang Q, Yan G and Cui Q. LncRNADisease: a database for longnon-coding RNA-associated diseases. Nucleic Acids Res. 2013; 41:D983-D986.
13. Khalil AM, Guttman M, Huarte M, Garber M, Raj A, Morales DR, Thomas K, Presser A, Bernstein BE and Van Oudenaarden A. Many human large intergenic noncoding RNAs associate with chromatin-modifying complexes and affect gene expression. P Natl Acad Sci USA. 2009; 106:11667-11672.
14. Yu F, Zheng J, Mao Y, Dong P, Li G, Lu Z, Guo C, Liu Z and Fan X. Long non-coding RNA APTR promotes the activation of hepatic stellate cells and the progression of liver fibrosis. Biochem Biophys Res Commun. 2015; 463:679-685.
15. Tsai M-C, Manor O, Wan Y, Mosammaparast N, Wang JK, Lan F, Shi Y, Segal E and Chang HY. Long noncoding RNA as modular scaffold of histone modification complexes. Science. 2010; 329:689-693.
16. Penny GD, Kay GF, Sheardown SA, Rastan S and Brockdorff N. Requirement for Xist in X chromosome inactivation. Nature. 1996; 379:131-137.
17. Fang Z, Wu L, Wang L, Yang Y, Meng Y and Yang H. Increased expression of the long non-coding RNA UCA1 in tongue squamous cell carcinomas: a possible correlation with cancer metastasis. Oral surgery, oral medicine, oral pathology and oral radiology. 2014; 117:89-95.
18. Salmena L, Poliseno L, Tay Y, Kats L and Pandolfi PP. A ceRNA hypothesis: the Rosetta Stone of a hidden RNA language? Cell. 2011; 146:353-358.
19. Alvarez ML and DiStefano JK. Functional characterization of the plasmacytoma variant translocation 1 gene (PVT1) in diabetic nephropathy. PLoS One. 2011; 6:e18671.
20. Pasmant E, Sabbagh A, Vidaud M and Bièche I. ANRIL, a long, noncoding RNA, is an unexpected major hotspot in GWAS. FASEB J. 2011; 25:444-448.
21. Zhang Q, Chen C-Y, Yedavalli VS and Jeang K-T. NEAT1 long noncoding RNA and paraspeckle bodies modulate HIV-1 posttranscriptional expression. MBio. 2013; 4:e00596-00512.
22. Guffanti A, Iacono M, Pelucchi P, Kim N, Soldà G, Croft LJ, Taft RJ, Rizzi E, Askarian-Amiri M and Bonnal RJ. A transcriptional sketch of a primary human breast cancer by 454 deep sequencing. BMC Genomics. 2009; 10:163.
23. Gupta RA, Shah N, Wang KC, Kim J, Horlings HM, Wong DJ, Tsai M-C, Hung T, Argani P and Rinn JL. Long noncoding RNA HOTAIR reprograms chromatin state to promote cancer metastasis. Nature. 2010; 464:1071-1076.
24. Zhang X, Zhou Y, Mehta KR, Danila DC, Scolavino S, Johnson SR and Klibanski A. A pituitary-derived MEG3 isoform functions as a growth suppressor in tumor cells. J Clin Endocrinol Metab. 2003; 88:5119-5126.
25. Ji P, Diederichs S, Wang W, Böing S, Metzger R, Schneider PM, Tidow N, Brandt B, Buerger H and Bulk E. MALAT-1, a novel noncoding RNA, and thymosin β4 predict metastasis and survival in early-stage non-small cell lung cancer. Oncogene. 2003; 22:8031-8041.
26. Pibouin L, Villaudy J, Ferbus D, Muleris M, Prospéri M-T, Remvikos Y and Goubin G. Cloning of the mRNA of overexpression in colon carcinoma-1: a sequence overexpressed in a subset of colon carcinomas. Cancer Genet Cytogenet. 2002; 133:55-60.
27. Zhang X, Lian Z, Padden C, Gerstein MB, Rozowsky J, Snyder M, Gingeras TR, Kapranov P, Weissman SM and Newburger PE. A myelopoiesis-associated regulatory intergenic noncoding RNA transcript within the human HOXA cluster. Blood. 2009; 113:2526-2534.
28. Guan Y, Kuo W-L, Stilwell JL, Takano H, Lapuk AV, Fridlyand J, Mao J-H, Yu M, Miller MA and Santos JL. Amplification of PVT1 contributes to the pathophysiology of ovarian and breast cancer. Clin Cancer Res. 2007; 13:5745-5755.
29. Feng FY, Ma T, Speers C, Iyer MK, Zhao S, Prensner JR, Rae JM, Pierce LJ and Chinnaiyan AM. Abstract PD6-1: The long noncoding RNA M41 promotes aggressiveness and tamoxifen resistance in ER-positive breast cancers. Cancer Res. 2015; 75:PD6-1-PD6-1.
30. Xu Z, Chen J, Luk JM and De W. LncRNA ANRIL indicates a potential prognostic biomarker in gastric cancer and promotes tumor growth by silencing of miR-99a/miR-449a. Cancer Res. 2015; 75:157-157.
31. Ochoa AE, Zhang J, Choi W, Malouf GG, Thompson EJ, Weinstein JN, Tannir NM, Dinney C, McConkey DJ and Su X. Abstract A1-68: The long noncoding RNA SNHG18 promotes PPAR? function and luminal gene expression in muscleinvasive bladder cancer. Cancer Res. 2015; 75:A1-68-A61-68.
32. Borsani G, Tonlorenzi R, Simmler MC, Dandolo L, Arnaud D, Capra V, Grompe M, Pizzuti A, Muzny D and Lawrence C. Characterization of a murine gene expressed from the inactive X chromosome. Nature. 1991; 351:325-329.
33. Brannan CI, Dees EC, Ingram RS and Tilghman SM. The product of the H19 gene may function as an RNA. Mol Cell Biol. 1990; 10:28-36.
34. Brockdorff N, Ashworth A, Kay GF, McCabe VM, Norris DP, Cooper PJ, Swift S and Rastan S. The product of the mouse Xist gene is a 15 kb inactive X-specific transcript containing no conserved ORF and located in the nucleus. Cell. 1992; 71:515-526.
35. Dinger ME, Pang KC, Mercer TR, Crowe ML, Grimmond SM and Mattick JS. NRED: a database of long noncoding RNA expression. Nucleic Acids Res. 2009; 37:D122-D126.
36. Bu D, Yu K, Sun S, Xie C, Skogerbø G, Miao R, Xiao H, Liao Q, Luo H and Zhao G. NONCODE v3.0: integrative annotation of long noncoding RNAs. Nucleic Acids Res. 2011; 40:D210-D215.
37. Chen X and Yan G-Y. Novel human lncRNA-disease association inference based on lncRNA expression profiles. Bioinformatics. 2013; 29:2617-2624.
38. Chen X. Predicting lncRNA-disease associations and constructing lncRNA functional similarity network based on the information of miRNA. Sci Rep. 2015; 5:13186.
39. Chen X. KATZLDA: KATZ measure for the lncRNAdisease association prediction. Sci Rep. 2015; 5:16840.
40. Liu M-X, Chen X, Chen G, Cui Q-H and Yan G-Y. A computational framework to infer human disease-associated long noncoding RNAs. PLoS One. 2014; 9:e84408.
41. Huang Y, Chen X, You Z, Huang D and Chan K. ILNCSIM: improved lncRNA functional similarity calculation model. Oncotarget. 2016; 7:25902-25914. doi: 10.18632/ oncotarget.8296.
42. Chen X, Yan CC, Zhang X, You Z-H, Deng L, Liu Y, Zhang Y and Dai Q. WBSMDA: Within and Between Score for MiRNA-Disease Association prediction. Scientific reports. 2016; 6:21106
43. Chen X. miREFRWR: a novel disease-related microRNAenvironmental factor interactions prediction method. Mol Biosyst. 2016; 12:624-633.
44. Chen X, Yan CC, Zhang X, Li Z, Deng L, Zhang Y and Dai Q. RBMMMDA: predicting multiple types of diseasemicroRNA associations. Sci Rep. 2015; 5:13877.
45. Chen X and Yan G-Y. Semi-supervised learning for potential human microRNA-disease associations inference. Sci Rep. 2014; 4:5501.
46. Chen X, Liu MX and Yan G. RWRMDA: predicting novel human microRNA-disease associations. Mol Biosyst. 2012; 8:2792-2798.
47. Sun L, Luo H, Liao Q, Bu D, Zhao G, Liu C, Liu Y and Zhao Y. Systematic study of human long intergenic noncoding RNAs and their impact on cancer. Sci China Life Sci. 2013; 56:324-334.
48. Shi X, Sun M, Liu H, Yao Y and Song Y. Long non-coding RNAs: a new frontier in the study of human diseases. Cancer letters. 2013; 339:159-166.
49. Batista PJ and Chang HY. Long noncoding RNAs: cellular address codes in development and disease. Cell. 2013; 152:1298-1307.
50. Bellucci M, Agostini F, Masin M and Tartaglia GG. Predicting protein associations with long noncoding RNAs. Nature Methods. 2011; 8:444-445.
51. Liao Q, Liu C, Yuan X, Kang S, Miao R, Xiao H, Zhao G, Luo H, Bu D and Zhao H. Large-scale prediction of long non-coding RNA functions in a coding-non-coding gene co-expression network. Nucleic Acids Res. 2011; 39:3864-3878.
52. Xiao Y, Lv Y, Zhao H, Gong Y, Hu J, Li F, Xu J, Bai J, Yu F and Li X. Predicting the Functions of Long Noncoding RNAs Using RNA-Seq Based on Bayesian Network. Biomed Res Int. 2015; 2015.
53. Wang JZ, Du Z, Payattakool R, Philip SY and Chen C-F. A new method to measure the semantic similarity of GO terms. Bioinformatics. 2007; 23:1274-1281.
54. Sun J, Shi H, Wang Z, Zhang C, Liu L, Wang L, He W, Hao D, Liu S and Zhou M. Inferring novel lncRNA-disease associations based on a random walk model of a lncRNA functional similarity network. Mol Biosyst. 2014; 10:2074-2081.
55. Chen X, Yan CC, Luo C, Ji W, Zhang Y and Dai Q. Constructing lncRNA functional similarity network based on lncRNA-disease associations and disease semantic similarity. Sci Rep. 2015; 5:11338.
56. Wang E, Zaman N, Mcgee S, Milanese J-S, Masoudi-Nejad A and O'Connor-McCourt M. (2015). Predictive genomics: A cancer hallmark network framework for predicting tumor clinical phenotypes using genome sequencing data. Semin Cancer Biol: Elsevier), pp. 4-12.
57. Li J, Lenferink AE, Deng Y, Collins C, Cui Q, Purisima EO, O'Connor-McCourt MD and Wang E. Identification of high-quality cancer prognostic markers and metastasis network modules. Nature communications. 2010; 1:34.
58. Masoudi-Nejad A and Wang E. (2015). Cancer modeling and network biology: Accelerating toward personalized medicine. Seminars in cancer biology: Elsevier), pp. 1-3.
59. Yu G, Li F, Qin Y, Bo X, Wu Y and Wang S. GOSemSim: an R package for measuring semantic similarity among GO terms and gene products. Bioinformatics. 2010; 26:976-978.
60. Fröhlich H, Speer N, Poustka A and Beißbarth T. GOSim-an R-package for computation of information theoretic GO similarities between terms and gene products. BMC bioinformatics. 2007; 8:166.
61. Luiten G, Froese T, Björk B, Cooper G, Junge R, Karstila K and Oxman R. An information reference model for architecture, engineering, and construction. Management of information technology for construction, World scientific & global publication services, Singapore. 1993; 1993:391-406.
62. Ye J. Multicriteria group decision-making method using vector similarity measures for trapezoidal intuitionistic fuzzy numbers. Group Decis Negot. 2012; 21:519-530.
63. Parvathi R and Malathi C. Arithmetic operations on symmetric trapezoidal intuitionistic fuzzy numbers. A A. 2012; 1:1.
64. Murofushi T and Sugeno M. An interpretation of fuzzy measures and the Choquet integral as an integral with respect to a fuzzy measure. Fuzzy Set Syst. 1989; 29:201-227.
65. Nguyen HT, Kreinovich V, Lorkowski J and Abu S. Why Sugeno lambda-Measures. 2015.
66. Wang Y, Chen L, Chen B, Li X, Kang J, Fan K, Hu Y, Xu J, Yi L and Yang J. Mammalian ncRNA-disease repository: a global view of ncRNA-mediated disease network. Cell Death Dis. 2013; 4:e765.
67. Ning S, Zhang J, Wang P, Zhi H, Wang J, Liu Y, Gao Y, Guo M, Yue M and Wang L. Lnc2Cancer: a manually curated database of experimentally supported lncRNAs associated with various human cancers. Nucleic Acids Res. 2015; 44:D980-D985.
68. Farag SS, Archer KJ, Mrózek K, Ruppert AS, Carroll AJ, Vardiman JW, Pettenati MJ, Baer MR, Qumsiyeh MB and Koduru PR. Pretreatment cytogenetics add to other prognostic factors predicting complete remission and longterm outcome in patients 60 years of age or older with acute myeloid leukemia: results from Cancer and Leukemia Group B 8461. Blood. 2006; 108:63-73.
69. Kantarjian H, O'Brien S, Cortes J, Giles F, Faderl S, Jabbour E, Garcia-Manero G, Wierda W, Pierce S and Shan J. Results of intensive chemotherapy in 998 patients age 65 years or older with acute myeloid leukemia or high-risk myelodysplastic syndrome. cancer. 2006; 106:1090-1098.
70. Schlenk RF, Döhner K, Krauter J, Fröhling S, Corbacioglu A, Bullinger L, Habdank M, Späth D, Morgan M and Benner A. Mutations and treatment outcome in cytogenetically normal acute myeloid leukemia. N Engl J Med. 2008; 358:1909-1918.
71. Gutschner T, Hämmerle M, Eißmann M, Hsu J, Kim Y, Hung G, Revenko A, Arun G, Stentrup M and Groß M. The noncoding RNA MALAT1 is a critical regulator of the metastasis phenotype of lung cancer cells. Cancer Res. 2013; 73:1180-1189.
72. Liu X-H, Liu Z-l, Sun M, Liu J, Wang Z-x and De W. The long non-coding RNA HOTAIR indicates a poor prognosis and promotes metastasis in non-small cell lung cancer. BMC Cancer. 2013; 13:464.
73. Enfield KS, Pikor LA, Martinez VD and Lam WL. Mechanistic roles of noncoding RNAs in lung cancer biology and their clinical implications. Genet Res Int 2012; 2012.
74. Wang H-M, Lu J-H, Chen W-Y and Gu A-Q. Upregulated lncRNA-UCA1 contributes to progression of lung cancer and is closely related to clinical diagnosis as a predictive biomarker in plasma. Int J Clin Exp Med. 2015; 8:11824-11830.
75. Lipscomb CE. Medical subject headings (MeSH). Bull Med Libr Assoc. 2000; 88:265-266.
76. Kruse R. A note on λ-additive fuzzy measures. Fuzzy Sets and Systems. 1982; 8:219-222.
77. Miranda P and Grabisch M. (2002). Caracterizing k-Additive Fuzzy Measures. Technologies for Constructing Intelligent Systems 2: Springer), pp. 209-222.
78. Al Boni M, Anderson DT and King RL. Hybrid Measure of Agreement and Expertise for Ontology Matching in Lieu of a Reference Ontology. International Journal of Intelligent Systems. 2015.
79. Štefka D and Holeňa M. Dynamic classifier aggregation using interaction-sensitive fuzzy measures. Fuzzy Sets and Systems. 2015; 270:25-52.