Network-Based Methods and Other Approaches for Predicting lncRNA Functions and Disease Associations

Part of the Methods in Molecular Biology book series (MIMB, volume 1912)


The discovery that a considerable portion of eukaryotic genomes is transcribed and gives rise to long noncoding RNAs (lncRNAs) provides an important new perspective on the transcriptome and raises questions about the centrality of these lncRNAs in gene-regulatory processes and diseases. The rapidly increasing number of mechanistically investigated lncRNAs has provided evidence for distinct functional classes, such as enhancer-like lncRNAs, which modulate gene expression via chromatin looping, and noncoding competing endogenous RNAs (ceRNAs), which act as microRNA decoys. Despite great progress in the last years, the majority of lncRNAs are functionally uncharacterized and their implication for disease biogenesis and progression is unknown. Here, we summarize recent developments in lncRNA function prediction in general and lncRNA–disease associations in particular, with emphasis on in silico methods based on network analysis and on ceRNA function prediction. We believe that such computational techniques provide a valuable aid to prioritize functional lncRNAs or disease-relevant lncRNAs for targeted, experimental follow-up studies.

Key words

lncRNA ceRNA Function prediction Disease-gene prediction Network analysis Chromatin interactions 



The authors kindly acknowledge Heike Siebert and Denise Thiel for insightful discussions. This study is supported by the DFG Grant MA 4454/3-1.


  1. 1.
    Djebali S et al (2012) Landscape of transcription in human cells. Nature 489(7414):101–108PubMedPubMedCentralGoogle Scholar
  2. 2.
    Costa FF (2005) Non-coding RNAs: new players in eukaryotic biology. Gene 357(2):83–94PubMedCrossRefGoogle Scholar
  3. 3.
    Bassett AR et al (2014) Considerations when investigating lncRNA function in vivo. eLife 3:e03058PubMedPubMedCentralCrossRefGoogle Scholar
  4. 4.
    Chen X et al (2017) Long non-coding RNAs and complex diseases: from experimental results to computational models. Brief Bioinform 18(4):558–576PubMedGoogle Scholar
  5. 5.
    The ENCODE Project Consortium (2012) An integrated encyclopedia of DNA elements in the human genome. Nature 489(7414):57–74PubMedCentralCrossRefGoogle Scholar
  6. 6.
    Harrow J et al (2012) GENCODE: the reference human genome annotation for The ENCODE Project. Genome Res 22(9):1760–1774PubMedPubMedCentralCrossRefGoogle Scholar
  7. 7.
    Xie C et al (2014) NONCODEv4: exploring the world of long non-coding RNA genes. Nucleic Acids Res 42(D1):D98–D103PubMedCrossRefPubMedCentralGoogle Scholar
  8. 8.
    Zhao Y et al (2016) NONCODEv4: annotation of noncoding RNAs with emphasis on long noncoding RNAs. Methods Mol Biol 1402:243–254PubMedCrossRefPubMedCentralGoogle Scholar
  9. 9.
    Ulitsky I, Bartel DP (2013) lincRNAs: genomics, evolution, and mechanisms. Cell 154(1):26–46PubMedPubMedCentralCrossRefGoogle Scholar
  10. 10.
    Quek XC et al (2015) lncRNAdb v2.0: expanding the reference database for functional long noncoding RNAs. Nucleic Acids Res 43(D1):D168–D173PubMedCrossRefGoogle Scholar
  11. 11.
    Bedoya-Reina OC, Ponting CP (2017) Functional RNA classes: a matter of time? Nat Struct Mol Biol 24(1):7–8PubMedCrossRefGoogle Scholar
  12. 12.
    Fang Y et al (2016) Mechanisms of long non-coding RNAs in cancer. Genomics Proteomics Bioinformatics 14(1):42–54PubMedPubMedCentralCrossRefGoogle Scholar
  13. 13.
    Mercer TR, Mattick JS (2013) Structure and function of long noncoding RNAs in epigenetic regulation. Nat Struct Mol Biol 20(3):300–307PubMedCrossRefGoogle Scholar
  14. 14.
    Rinn JL, Chang HY (2012) Genome regulation by long noncoding RNAs. Annu Rev Biochem 81(1):145–166PubMedPubMedCentralCrossRefGoogle Scholar
  15. 15.
    Gendrel AV et al (2014) Noncoding RNAs and epigenetic mechanisms during X-chromosome inactivation. Annu Rev Cell Dev Biol 30:561–580PubMedCrossRefGoogle Scholar
  16. 16.
    Sandhu KS et al (2012) Large-scale functional organization of long-range chromatin interaction networks. Cell Rep 2(5):1207–1219PubMedPubMedCentralCrossRefGoogle Scholar
  17. 17.
    Dekker J et al (2015) Long-range chromatin interactions. Cold Spring Harb Perspect Biol 7(10):a019356PubMedPubMedCentralCrossRefGoogle Scholar
  18. 18.
    Ørom UA et al (2010) Long noncoding RNAs with enhancer-like function in human cells. Cell 143(1):46–58PubMedPubMedCentralCrossRefGoogle Scholar
  19. 19.
    Ntini E et al (2018) Long ncRNA A-ROD activates its target gene DKK1 at its release from chromatin. Nat Commun 9(1):1636PubMedPubMedCentralCrossRefGoogle Scholar
  20. 20.
    Heller D et al (2017) ssHMM: extracting intuitive sequence structure motifs from high-throughput RNA-binding protein data. Nucleic Acids Res 45(19):11004–11018PubMedPubMedCentralCrossRefGoogle Scholar
  21. 21.
    Krakau S et al (2017) PureCLIP: capturing target-specific protein-RNA interaction footprints from single nucleotide CLIP-seq data. Genome Biol 18(1):240PubMedPubMedCentralCrossRefGoogle Scholar
  22. 22.
    Budach S, Marsico A (2018) Pysster: classification of biological sequences by learning sequence and structure motifs with convolutional neural networks. Bioinformatics 34(17):3035–3037PubMedPubMedCentralCrossRefGoogle Scholar
  23. 23.
    Poliseno L et al (2010) A coding-independent function of gene and pseudogene mRNAs regulates tumour biology. Nature 465:1033–1038PubMedPubMedCentralCrossRefGoogle Scholar
  24. 24.
    Salmena L et al (2011) A ceRNA hypothesis: the Rosetta Stone of a hidden RNA language? Cell 146(3):353–358PubMedPubMedCentralCrossRefGoogle Scholar
  25. 25.
    Ebert MS et al (2007) MicroRNA sponges: competitive inhibitors of small RNAs in mammalian cells. Nat Methods 4:721–726PubMedCrossRefGoogle Scholar
  26. 26.
    Franco-Zorrilla JM et al (2007) Target mimicry provides a new mechanism for regulation of microRNA activity. Nat Genet 39(8):1033–1037PubMedCrossRefGoogle Scholar
  27. 27.
    Karreth FA, Pandolfi PP (2013) ceRNA cross-talk in cancer: when ce-bling rivalries go awry. Cancer Discov 3(10):1113–1121PubMedPubMedCentralCrossRefGoogle Scholar
  28. 28.
    Piro RM (2011) Are all genes regulatory genes? Biol Philos 26(4):595–602CrossRefGoogle Scholar
  29. 29.
    Cesana M et al (2011) A long noncoding RNA controls muscle differentiation by functioning as a competing endogenous RNA. Cell 147(2):358–369PubMedPubMedCentralCrossRefGoogle Scholar
  30. 30.
    Paci P, Colombo T, Farina L (2014) Computational analysis identifies a sponge interaction network between long non-coding RNAs and messenger RNAs in human breast cancer. BMC Syst Biol 8(1):83PubMedPubMedCentralCrossRefGoogle Scholar
  31. 31.
    Tay Y et al (2011) Coding-independent regulation of the tumor suppressor PTEN by competing endogenous mRNAs. Cell 147(2):344–357PubMedPubMedCentralCrossRefGoogle Scholar
  32. 32.
    Yang C et al (2016) Competing endogenous RNA networks in human cancer: hypothesis, validation, and perspectives. Oncotarget 7(12):13479–13490PubMedPubMedCentralCrossRefGoogle Scholar
  33. 33.
    Qu L et al (2016) Exosome-transmitted lncARSR promotes sunitinib resistance in renal cancer by acting as a competing endogenous RNA. Cancer Cell 29(5):653–668PubMedCrossRefPubMedCentralGoogle Scholar
  34. 34.
    Chan JJ, Tay Y (2018) Noncoding RNA:RNA regulatory networks in cancer. Int J Mol Sci 19(5):1310PubMedCentralCrossRefGoogle Scholar
  35. 35.
    Tay Y, Rinn J, Pandolfi PP (2014) The multilayered complexity of ceRNA crosstalk and competition. Nature 505(7483):344–352PubMedPubMedCentralCrossRefGoogle Scholar
  36. 36.
    Anastasiadou E, Jacob LS, Slack FJ (2018) Non-coding RNA networks in cancer. Nat Rev Cancer 18(1):5–18CrossRefGoogle Scholar
  37. 37.
    Taulli R, Loretelli C, Pandolfi PP (2013) From pseudo-ceRNAs to circ-ceRNAs: a tale of cross-talk and competition. Nat Struct Mol Biol 20:541–543PubMedPubMedCentralCrossRefGoogle Scholar
  38. 38.
    Ala U et al (2013) Integrated transcriptional and competitive endogenous RNA networks are cross-regulated in permissive molecular environments. Proc Natl Acad Sci 110(18):7154–7159PubMedCrossRefPubMedCentralGoogle Scholar
  39. 39.
    Figliuzzi M, Marinari E, De Martino A (2013) MicroRNAs as a selective channel of communication between competing RNAs: a steady-state theory. Biophys J 104(5):1203–1213PubMedPubMedCentralCrossRefGoogle Scholar
  40. 40.
    Smillie CL, Sirey T, Ponting CP (2018) Complexities of post-transcriptional regulation and the modeling of ceRNA crosstalk. Crit Rev Biochem Mol Biol 53(3):231–245PubMedPubMedCentralCrossRefGoogle Scholar
  41. 41.
    Bosson AD, Zamudio JR, Sharp PA (2014) Endogenous miRNA and target concentrations determine susceptibility to potential ceRNA competition. Mol Cell 56(3):347–359PubMedPubMedCentralCrossRefGoogle Scholar
  42. 42.
    Tan JY et al (2015) Extensive microRNA-mediated crosstalk between lncRNAs and mRNAs in mouse embryonic stem cells. Genome Res 25(5):655–666PubMedPubMedCentralCrossRefGoogle Scholar
  43. 43.
    Denzler R et al (2014) Assessing the ceRNA hypothesis with quantitative measurements of miRNA and target abundance. Mol Cell 54(5):766–776PubMedPubMedCentralCrossRefGoogle Scholar
  44. 44.
    Kartha RV, Subramanian S (2014) Competing endogenous RNAs (ceRNAs): new entrants to the intricacies of gene regulation. Front Genet 5:8PubMedPubMedCentralCrossRefGoogle Scholar
  45. 45.
    Esteller M (2011) Non-coding RNAs in human disease. Nat Rev Genet 12(12):861–874CrossRefGoogle Scholar
  46. 46.
    Yang F et al (2011) Long noncoding RNA high expression in hepatocellular carcinoma facilitates tumor growth through enhancer of zeste homolog 2 in humans. Hepatology 54(5):1679–1689PubMedCrossRefGoogle Scholar
  47. 47.
    Tessier CR et al (2004) Mammary tumor induction in transgenic mice expressing an RNA-binding protein. Cancer Res 64(1):209–214PubMedCrossRefPubMedCentralGoogle Scholar
  48. 48.
    Mourtada-Maarabouni M et al (2009) GAS5, a non-protein-coding RNA, controls apoptosis and is downregulated in breast cancer. Oncogene 28(2):195–208PubMedCrossRefPubMedCentralGoogle Scholar
  49. 49.
    Guan Y et al (2007) Amplification of PVT1 contributes to the pathophysiology of ovarian and breast cancer. Clin Cancer Res 13(19):5745–5755PubMedCrossRefPubMedCentralGoogle Scholar
  50. 50.
    Chen W et al (1997) Expression of neural BC200 RNA in human tumours. J Pathol 183(3):345–351PubMedCrossRefGoogle Scholar
  51. 51.
    Faghihi MA et al (2008) Expression of a noncoding RNA is elevated in Alzheimer’s disease and drives rapid feed-forward regulation of beta-secretase. Nat Med 14(7):723–730PubMedPubMedCentralCrossRefGoogle Scholar
  52. 52.
    Zhang A et al (2014) Role of the lncRNA-p53 regulatory network in cancer. Mol Cell Biol 6(3):181–191CrossRefGoogle Scholar
  53. 53.
    Cheng G et al (2013) LncRNADisease: a database for long-non-coding RNA-associated diseases. Nucleic Acids Res 41(Database issue):D983–D986Google Scholar
  54. 54.
    Ning S et al (2016) Lnc2Cancer: a manually curated database of experimentally supported lncRNAs associated with various human cancers. Nucleic Acids Res 44(D1):D980–D985CrossRefGoogle Scholar
  55. 55.
    Ning S et al (2014) SNP@lincTFBS: an integrated database of polymorphisms in human lincRNA transcription factor binding sites. PLoS One 9(7):e103851PubMedPubMedCentralCrossRefGoogle Scholar
  56. 56.
    Gong J et al (2015) lncRNASNP: a database of SNPs in lncRNAs and their potential functions in human and mouse. Nucleic Acids Res 43(Database issue):D181–D186PubMedCrossRefGoogle Scholar
  57. 57.
    Cabili MN et al (2011) Integrative annotation of human large intergenic noncoding RNAs reveals global properties and specific subclasses. Genes Dev 25(18):1915–1927PubMedPubMedCentralCrossRefGoogle Scholar
  58. 58.
    Iyer MK et al (2015) The landscape of long noncoding RNAs in the human transcriptome. Nat Genet 47(3):199–208PubMedPubMedCentralCrossRefGoogle Scholar
  59. 59.
    Guo X et al (2016) Advances in long noncoding RNAs: identification, structure prediction and function annotation. Brief Funct Genomics 15(1):38–46PubMedCrossRefGoogle Scholar
  60. 60.
    Fiscon G, Paci P, Iannello G (2015) MONSTER v1.1: a tool to extract and search for RNA non-branching structures. BMC Genomics 16(6):S1PubMedPubMedCentralCrossRefGoogle Scholar
  61. 61.
    Wilusz JE, Freier SM, Spector DL (2008) 3’ end processing of a long nuclear-retained noncoding RNA yields a tRNA-like cytoplasmic RNA. Cell 135(5):919–932PubMedPubMedCentralCrossRefGoogle Scholar
  62. 62.
    Stuart JM et al (2003) A gene-coexpression network for global discovery of conserved genetic modules. Science 302(5643):249–255PubMedCrossRefGoogle Scholar
  63. 63.
    Barabási AL, Albert R (1999) Emergence of scaling in random networks. Science 286(5439):509–512PubMedCrossRefGoogle Scholar
  64. 64.
    Liao Q et al (2011) Large-scale prediction of long non-coding RNA functions in a coding–non-coding gene co-expression network. Nucleic Acids Res 39(9):3864–3878PubMedPubMedCentralCrossRefGoogle Scholar
  65. 65.
    Spicuglia S et al (2013) An update on recent methods applied for deciphering the diversity of the noncoding RNA genome structure and function. Methods 63(1):3–17PubMedCrossRefGoogle Scholar
  66. 66.
    Signal B, Gloss BS, Dinger ME (2016) Computational approaches for functional prediction and characterisation of long noncoding RNAs. Trends Genet 32(10):620–637PubMedCrossRefGoogle Scholar
  67. 67.
    Chen X, Yan G-Y (2013) Novel human lncRNA–disease association inference based on lncRNA expression profiles. Bioinformatics 29(20):2617–2624PubMedCrossRefGoogle Scholar
  68. 68.
    Chen X et al (2015) Constructing lncRNA functional similarity network based on lncRNA-disease associations and disease semantic similarity. Sci Rep 5:11338PubMedPubMedCentralCrossRefGoogle Scholar
  69. 69.
    Zhao T et al (2015) Identification of cancer-related lncRNAs through integrating genome, regulome and transcriptome features. Mol BioSyst 11:126–136PubMedCrossRefGoogle Scholar
  70. 70.
    Sun J et al (2014) Inferring novel lncRNA-disease associations based on a random walk model of a lncRNA functional similarity network. Mol BioSyst 10:2074–2081PubMedCrossRefPubMedCentralGoogle Scholar
  71. 71.
    Chen X et al (2012) Prediction of disease-related interactions between microRNAs and environmental factors based on a semi-supervised classifier. PLoS One 7(8):e43425PubMedPubMedCentralCrossRefGoogle Scholar
  72. 72.
    Huang YA et al (2016) ILNCSIM: improved lncRNA functional similarity calculation model. Oncotarget 7(18):25902–25914PubMedPubMedCentralGoogle Scholar
  73. 73.
    Ganegoda GU et al (2015) Heterogeneous network model to infer human disease-long intergenic non-coding RNA associations. IEEE Trans NanoBiosci 14(2):175–183CrossRefGoogle Scholar
  74. 74.
    Liu M-X et al (2014) A computational framework to infer human disease-associated long noncoding RNAs. PLoS One 9(1):e84408PubMedPubMedCentralCrossRefGoogle Scholar
  75. 75.
    Cheng L et al (2016) IntNetLncSim: an integrative network analysis method to infer human lncRNA functional similarity. Oncotarget 7(30):47864–47874PubMedPubMedCentralGoogle Scholar
  76. 76.
    Perron U, Provero P, Molineris I (2017) In silico prediction of lncRNA function using tissue specific and evolutionary conserved expression. BMC Bioinf 18(Suppl 5):144CrossRefGoogle Scholar
  77. 77.
    Gu C et al (2017) Global network random walk for predicting potential human lncRNA-disease associations. Sci Rep 7(1):12442PubMedPubMedCentralCrossRefGoogle Scholar
  78. 78.
    Welter D et al (2014) The NHGRI GWAS Catalog, a curated resource of SNP-trait associations. Nucleic Acids Res 42(Database issue):D1001–D1006PubMedCrossRefGoogle Scholar
  79. 79.
    Barrett T et al (2013) NCBI GEO: archive for functional genomics data sets–update. Nucleic Acids Res 41(D1):D991–D995PubMedCrossRefGoogle Scholar
  80. 80.
    Guo X et al (2013) Long non-coding RNAs function annotation: a global prediction method based on bi-colored networks. Nucleic Acids Res 41(2):e35PubMedCrossRefGoogle Scholar
  81. 81.
    Ala U et al (2008) Prediction of human disease genes by human-mouse conserved coexpression analysis. PLOS Comput Biol 4(3):e1000043PubMedPubMedCentralCrossRefGoogle Scholar
  82. 82.
    Piro RM et al (2011) An atlas of tissue-specific conserved coexpression for functional annotation and disease gene prediction. Eur J Hum Genet 19(11):1173–1180PubMedPubMedCentralCrossRefGoogle Scholar
  83. 83.
    Piro RM (2012) Network medicine: linking disorders. Hum Genet 131(12):1811–1820PubMedCrossRefGoogle Scholar
  84. 84.
    Zhou M et al (2015) Prioritizing candidate disease-related long non-coding RNAs by walking on the heterogeneous lncRNA and disease network. Mol Biosyst 11(3):760–769PubMedCrossRefGoogle Scholar
  85. 85.
    Chen X et al (2015) KATZLDA: KATZ measure for the lncRNA-disease association prediction. Sci Rep 5:16840PubMedPubMedCentralCrossRefGoogle Scholar
  86. 86.
    Li J-H et al (2014) starBase v2.0: decoding miRNA-ceRNA, miRNA-ncRNA and protein–RNA interaction networks from large-scale CLIP-Seq data. Nucleic Acids Res 42(D1):D92–D97PubMedCrossRefGoogle Scholar
  87. 87.
    Keshava Prasad TS et al (2009) Human Protein Reference Database–2009 update. Nucleic Acids Res 37(Database issue):D767–D772PubMedCrossRefPubMedCentralGoogle Scholar
  88. 88.
    Vergoulis T et al (2012) TarBase 6.0: capturing the exponential growth of miRNA targets with experimental support. Nucleic Acids Res 40(D1):D222–D229PubMedCrossRefGoogle Scholar
  89. 89.
    Hsu S-D et al (2014) miRTarBase update 2014: an information resource for experimentally validated miRNA-target interactions. Nucleic Acids Res 42(D1):D78–D85PubMedCrossRefPubMedCentralGoogle Scholar
  90. 90.
    Xiao F et al (2009) miRecords: an integrated resource for microRNA–target interactions. Nucleic Acids Res 37(Database issue):D105–D110CrossRefGoogle Scholar
  91. 91.
    Stojmirovic A, Yu YK (2009) ITM Probe: analyzing information flow in protein networks. Bioinformatics 25(18):2447–2449PubMedPubMedCentralCrossRefGoogle Scholar
  92. 92.
    Siahpirani A et al (2016) A multi-task graph-clustering approach for chromosome conformation capture data sets identifies conserved modules of chromosomal interactions. Genome Biol 17(1):114CrossRefGoogle Scholar
  93. 93.
    Li G et al (2010) ChIA-PET tool for comprehensive chromatin interaction analysis with paired-end tag sequencing. Genome Biol 11(2):R22PubMedPubMedCentralCrossRefGoogle Scholar
  94. 94.
    Thiel D et al (2018) Identifying lncRNA-mediated regulatory modules via ChIA-PET network analysis. bioRxivGoogle Scholar
  95. 95.
    Lai F et al (2013) Activating RNAs associate with Mediator to enhance chromatin architecture and transcription. Nature 494(7438):497–501PubMedPubMedCentralCrossRefGoogle Scholar
  96. 96.
    Djurdjevac N et al (2011) Random walks on complex modular networks. J Numer Anal Ind Appl Math 6:29–50Google Scholar
  97. 97.
    Le TD et al (2017) Computational methods for identifying miRNA sponge interactions. Brief Bioinform 18(4):577–590PubMedGoogle Scholar
  98. 98.
    Thomas M, Lieberman J, Lal A (2010) Desperately seeking microRNA targets. Nat Struct Mol Biol 17(10):1169–1174PubMedCrossRefGoogle Scholar
  99. 99.
    Krek A et al (2005) Combinatorial microRNA target predictions. Nat Genet 37(5):495–500PubMedPubMedCentralCrossRefGoogle Scholar
  100. 100.
    Agarwal V et al (2015) Predicting effective microRNA target sites in mammalian mRNAs. eLife 4:e05005Google Scholar
  101. 101.
    Miranda KC et al (2006) A pattern-based method for the identification of microRNA binding sites and their corresponding heteroduplexes. Cell 126(6):1203–1217PubMedCrossRefGoogle Scholar
  102. 102.
    Kertesz M et al (2007) The role of site accessibility in microRNA target recognition. Nat Genet 39(10):1278–1284PubMedCrossRefGoogle Scholar
  103. 103.
    Riffo-Campos ÁL, Riquelme I, Brebi-Mieville P (2016) Tools for sequence-based miRNA target prediction: what to choose? Int J Mol Sci 17(12):1987PubMedCentralCrossRefPubMedGoogle Scholar
  104. 104.
    Bhartiya D et al (2013) lncRNome: a comprehensive knowledgebase of human long noncoding RNAs. Database 2013:bat034Google Scholar
  105. 105.
    Jeggari A, Marks DS, Larsson E (2012) miRcode: a map of putative microRNA target sites in the long non-coding transcriptome. Bioinformatics 28(15):2062–2063PubMedPubMedCentralCrossRefGoogle Scholar
  106. 106.
    Paraskevopoulou MD et al (2013) DIANA-LncBase: experimentally verified and computationally predicted microRNA targets on long non-coding RNAs. Nucleic Acids Res 41(D1):D239–D245PubMedCrossRefGoogle Scholar
  107. 107.
    Zisoulis DG et al (2010) Comprehensive discovery of endogenous Argonaute binding sites in Caenorhabditis elegans. Nat Struct Mol Biol 17(2):173–179PubMedPubMedCentralCrossRefGoogle Scholar
  108. 108.
    Clark PM et al (2014) Argonaute CLIP-Seq reveals miRNA targetome diversity across tissue types. Sci Rep 4:5947PubMedPubMedCentralCrossRefGoogle Scholar
  109. 109.
    Joshua-Tor L (2006) The Argonautes. Cold Spring Harb Symp Quant Biol 71:67–72PubMedCrossRefGoogle Scholar
  110. 110.
    Kawamata T, Tomari Y (2010) Making RISC. Trends Biochem Sci 35(7):368–376PubMedCrossRefPubMedCentralGoogle Scholar
  111. 111.
    Sarver AL, Subramanian S (2012) Competing endogenous RNA database. Bioinformation 8(15):731–733PubMedPubMedCentralCrossRefGoogle Scholar
  112. 112.
    Sumazin P et al (2011) An extensive microRNA-mediated network of RNA-RNA interactions regulates established oncogenic pathways in glioblastoma. Cell 147(2):370–381PubMedPubMedCentralCrossRefGoogle Scholar
  113. 113.
    Chiu H-S et al (2015) Cupid: simultaneous reconstruction of microRNA-target and ceRNA networks. Genome Res 25(2):257–267PubMedPubMedCentralCrossRefGoogle Scholar
  114. 114.
    Zarringhalam K et al (2017) Identification of competing endogenous RNAs of the tumor suppressor gene PTEN: a probabilistic approach. Sci Rep 7(1):7755PubMedPubMedCentralCrossRefGoogle Scholar
  115. 115.
    Das S et al (2014) lnCeDB: database of human long noncoding RNA acting as competing endogenous RNA. PLoS One 9(6):e98965PubMedPubMedCentralCrossRefGoogle Scholar
  116. 116.
    Wang P et al (2015) miRSponge: a manually curated database for experimentally supported miRNA sponges and ceRNAs. Database 2015:bav098PubMedPubMedCentralCrossRefGoogle Scholar
  117. 117.
    Wang P et al (2015) Identification of lncRNA-associated competing triplets reveals global patterns and prognostic markers for cancer. Nucleic Acids Res 43(7):3478–3489PubMedPubMedCentralCrossRefGoogle Scholar
  118. 118.
    Piro RM, Di Cunto F (2012) Computational approaches to disease-gene prediction: rationale, classification and successes. FEBS J 279(5):678–696PubMedCrossRefGoogle Scholar
  119. 119.
    Xu C et al (2017) LncNetP, a systematical lncRNA prioritization approach based on ceRNA and disease phenotype association assumptions. Oncotarget 8(70):114603–114612PubMedPubMedCentralGoogle Scholar
  120. 120.
    Köhler S et al (2008) Walking the interactome for prioritization of candidate disease genes. Am J Hum Genet 82(4):949–958PubMedPubMedCentralCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Institut für InformatikFreie Universität BerlinBerlinGermany
  2. 2.Institut für Medizinische Genetik und HumangenetikCharité-Universitätsmedizin BerlinBerlinGermany
  3. 3.Max-Planck-Institut für molekulare GenetikBerlinGermany

Personalised recommendations