miRNAs target databases: developmental methods and target identification techniques with functional annotations

Cellular and Molecular Life Sciences

Volumn 74, Issue 12, 2017, Pages 2239-2261

  Singh, Nagendra Kumar ^a  

^a MAULANA AZAD NATIONAL INSTITUTE OF TECHNOLOGY   (India)

Author keywords

Bioinformatics; Biomarker; Data mining; Genome; High throughput; Pathology

Indexed keywords

MICRORNA;

3' UNTRANSLATED REGION; ALGORITHM; BIOGENESIS; DATA BASE; GENE CONTROL; GENETIC ASSOCIATION; HUMAN; IMMUNOHISTOCHEMISTRY; LUCIFERASE ASSAY; MICROARRAY ANALYSIS; NONHUMAN; REAL TIME POLYMERASE CHAIN REACTION; REVIEW; RNA ANALYSIS; SINGLE NUCLEOTIDE POLYMORPHISM; WESTERN BLOTTING; ANIMAL; BIOLOGICAL MODEL; BIOLOGY; GENETIC DATABASE; GENETICS; METABOLISM; MOLECULAR GENETICS;

ANIMALS; COMPUTATIONAL BIOLOGY; DATABASES, GENETIC; HUMANS; MICRORNAS; MODELS, GENETIC; MOLECULAR SEQUENCE ANNOTATION; POLYMORPHISM, SINGLE NUCLEOTIDE;

EID: 85012893638     PISSN: 1420682X     EISSN: 14209071     Source Type: Journal    
DOI: 10.1007/s00018-017-2469-1     Document Type: Review

References (123)

1. Bartel DP (2004) MicroRNAs: genomics, biogenesis, mechanism, and function. Cell 16:281–297. doi:10.1016/S0092-8674(04)00045-5
2. Almeida MI, Reis RM, Calin GA (2011) MicroRNA history: discovery, recent applications and next frontiers. Mutat Res 717:1–8. doi:10.1016/j.mrfmmm.2011.03.009
3. Lee RC, Feinbaum RL, Ambros V (1993) The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14. Cell 75:843–854. Doi:10.1016/0092-8674(93)90529-Y
4. Reinhart BJ, Slack FJ, Basson M, Pasquinelli AE et al (2000) The 21-nucleotide let-7 RNA regulates developmental timing in Caenorhabditiselegans. Nature 403:901–906. doi:10.1038/35002607
5. Brennecke J, Hipfner DR, Stark A, Russell RB, Cohen SM (2003) Bantam encodes a developmentally regulated microRNA that controls cell proliferation and regulates the proapoptotic gene hid in Drosophila. Cell 113:25–36. doi:10.1016/S0092-8674(03)00231-9
6. Ambros V (2004) The functions of animal micrornas. Nature 431(350):355. doi:10.1038/nature02871
7. Du T, Zamore PD (2007) Beginning to understand microrna function. Cell Res 17:661–663. doi:10.1038/cr.2007.67
8. Bushati N, Cohen SM (2007) Microrna functions. Annu Rev Cell Dev Bi 23:175–205.doi:10.1146/annurev.cellbio.23.090506.123406
9. Khraiwesh B, Zhu JK, Zhu J (2012) Role of miRNAs and siRNAs in biotic and abiotic stress responses of plants. Biochimica Biophysica Acta 1819:137–148. doi:10.1016/j.bbagrm.2011.05.001.
10. Kloosterman WP, Plasterk RH (2006) The diverse functions of MicroRNAs in animal development and disease. Dev Cell 11:441–450. doi:10.1016/j.devcel.2006.09.009
11. Jacobsen A, Silber J, Harinath G, Huse JT, Schultz N, Sander C (2013) Analysis of microRNA-target interactions across diverse cancer types. Nat Struct Mol Biol 20:1325–1332. doi:10.1038/nsmb.2678
12. Eckardt NA (2012) A microRNA cascade in plant defense. Plant Cell 24:840–840. doi:10.1105/tpc.112.240311
13. Singh Y, Kaul V, Mehra A, Chatterjee S, Tousif S, Dwivedi VP et al (2013) Mycobacterium tuberculosis controls microRNA-99b (miR-99b) expression in infected murine dendritic cells to modulate host immunity. J Biol Chem 288(7):5056–5061. doi:10.1074/jbc.C112.439778
14. Jansson MD, Lund AH (2012) MicroRNA and cancer. Mol Oncol 6:590–610. doi:10.1016/j.molonc.2012.09.006
15. Kumar P, Dezso Z, MacKenzie C, Oestreicher J, Agoulnik S et al (2013) Circulating miRNA Biomarkers for Alzheimer’s disease. PLoS ONE 8:e69807. doi:10.1371/journal.pone.0069807
16. Bej S, Basak J (2014) MicroRNAs: the potential biomarkers in plant stress response. Am J Plant Sci 5:748–759. doi:10.4236/ajps.2014.55089.
17. Nelson PT, Wang WX, Bernard WR (2008) MicroRNAs (miRNAs) in neurodegenerative diseases. Brain Pathol 18:130–138. doi:10.1111/j.1750-3639.2007.00120.x
18. Qu Z, Li W, Fu B (2014) MicroRNAs in Autoimmune Diseases. BioMed Res Int 2014:8. doi:10.1155/2014/527895
19. Shantikumar S, Caporali A, Emanueli C (2011) Role of miRNA in diabetes and its cardiovascular complications. Cardiovasc Res 93:583–593 doi:10.1093/cvr/cvr300
20. Mao Y, Mohan R, Zhang S, Tang X (2013) MicroRNAs as pharmacological targets in diabetes. Pharmaco Res 75:37–47. doi:10.1016/j.phrs.2013.06.005
21. Pauley KM, Cha S, Chan EK (2009) MicroRNA in autoimmunity and autoimmune diseases. J Autoimmun 32:189–194. doi:10.1016/j.jaut.2009.02.012
22. Farazi TA, Hoell JI, Morozov et al (2013) MicroRNAs in human cancer. Adv Exp Med Biol 774:1–20. doi:10.1007/978-94-007-5590-1
23. Duskova K, Nagilla P, Le H, Iyer P, Thalamuthu A et al (2013) MicroRNA regulation and its effects on cellular transcriptome in human immunodeficiency virus-1 (HIV-1) infected individuals with distinct viral load and CD4 cell counts. BMC Infect Dis 13:250. doi:10.1186/1471-2334-13-250
24. Lindsay MA (2003) Target discovery. Nat Rev Drug Discov 2:831–838. doi:10.1038/nrd1202
25. Yang Y, Adelstein SJ, Kassis AI (2009) Target discovery from data mining approaches. Drug Discov Today 14:147–154. doi:10.1016/j.drudis.2008.12.005
26. Ji X, Takahashi R, Hiura Y, Hirokawa G, Fukushima Y, Iwai N (2009) Plasma miR-208 as biomarker of myocardial injury. Clin Chem 55:1944–1949. doi:10.1373/clinchem.2009.125310
27. Hulanicka M, Garncarz M, Parzeniecka-Jaworska M, Jank M (2014) Plasma miRNAs as potential biomarkers of chronic degenerative valvular disease in Dachshunds. BMC Vet Res 10:205–208. doi:10.1186/s12917-014-0205-8
28. Spadaro PA, Bredy TW (2012) Emerging role of non-coding RNA in neural plasticity cognitive function and neuropsychiatric disorders. Front Genet 3:132. doi:10.3389/fgene.2012.00132
29. Finnegan EF, Pasquinelli AE (2013) MicroRNA biogenesis: regulating the regulators. Crit Rev Biochem Mol Biol 48:51–68. doi:10.3109/10409238.2012.738643
30. Ekimler S. Sahin K (2014) Computational methods for MicroRNA target prediction. Genes 5: 671–68. doi:10.3390/genes5030671.
31. Dimitrov R (2014) microRNA gene finding and target prediction—basic principles and challenges. MOJ Proteomics Bioinform 1:00024. doi:10.15406/mojpb.2014.01.00024.
32. Dónal C, Schaefer A (2012) General principals of miRNA biogenesis and regulation in the brain. Neuropsychopharmacol 38: 39–54. doi:10.1038/npp.2012.87.
33. Voinnet O (2009) Origin, biogenesis and activity of plant microRNAs. Cell 136:669–687. doi:10.1016/j.cell.2009.01.046
34. Martinez-Sanchez A, Murphy CL (2013) MicroRNA target identification—experimental approaches. Biology 2:189–205. doi:10.3390/biology2010189.
35. Thomson DW, Bracken CP, Goodall GJ (2014) Experimental strategies for microRNA target identification. Nucleic Acids Res 39:6845–6853. doi:10.1093/nar/gkr330
36. Ahmadi H, Ahmadi A, Azimzadeh-Jamalkandi S, Shoorehdeli MA, Salehzadeh-Yazdi A et al (2013) Homotarget: a new algorithm for prediction of microRNA targets in Homo sapiens. Genomics 101:94–100. doi:10.1016/j.ygeno.2012.11.005
37. Reyes-Herrera PH, Ficarra E (2012) One Decade of development and evolution of MicroRNA target prediction algorithms. Genom Proteom Bioinform 10:254–263. Doi:10.1016/j.gpb.2012.10.001
38. Srivastava PK, Moturu TR, Pandey P, Baldwin IT, Pandey SP (2014) A comparison of performance of plant miRNA target prediction tools and the characterization of features for genome-wide target prediction. BMC Genom 15:348.doi:10.1186/1471-2164-15-348
39. Peterson SM, Thompson JA, Ufkin ML, Sathyanarayana P et al (2014) Common features of microRNA target prediction tools. Front Genet 5:13 doi:10.3389/fgene.2014.00023
40. Dai X, Zhao PX (2011) psRNATarget: a plant small RNA target analysis server. Nucleic Acids Res 39:W155–W159. doi:10.1093/nar/gkr319
41. Wu HJ, Ma YK, Chen T, Wang M, Wang XJ (2012) PsRobot: a web-based plant small RNA meta-analysis toolbox. Nucleic Acids Res 40:W22–W28. doi:10.1093/nar/gks554
42. Bonnet E, He Y, Billiau K, Van de Peer Y(2010) TAPIR, a web server for the prediction of plant microRNA targets, including target mimics. Bioinformatics 26:1566–1568. doi:10.1093/bioinformatics/btq233
43. Bonnet E, Wuyts J, Rouzé P, Van de Peer Y (2004) Detection of 91 potential conserved plant microRNAs in Arabidopsis thaliana and Oryza sativaidentifies important target genes. PNAS 101:11511–11516. doi:10.1073/pnas.0404025101
44. Zhang Y (2005) miRU: an automated plant miRNA target prediction server. Nucleic Acids Res 33:W701–W704. doi:10.1093/nar/gki383
45. Fahlgren N, Howell MD, Kasschau KD, Chapman EJ, Sullivan CM et al (2007) High-throughput sequencing of Arabidopsis microRNAs: evidence for frequent birth and death of MIRNA genes. PLoS One 2:e219. doi:10.1371/journal.pone.0000219
46. Allen E, Xie Z, Gustafson AM, Carrington JC (2005) microRNA-directed phasing during trans-acting siRNA biogenesis in plants. Cell 121:207–221. doi:10.1016/j.cell.2005.04.004
47. Xie F, Zhang B (2010) Target-align: a tool for plant microRNA target identification. Bioinformatics 26(23):3002–3003. doi:10.1093/bioinformatics/btq568
48. Sun YH, Lu S, Shi R, Chiang VL (2011) Computational Prediction of Plant miRNATargets. Methods Mol Biol 744:175–186. doi:10.1007/978-1-61779-123-9_12
49. Jha A, Shankar R (2011) Employing machine learning for reliable miRNA target identification in plants. BMC Genomics 12:636. doi:10.1186/1471-2164-12-636
50. Lewis BP, Burge CB, Bartel DP (2005) Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are MicroRNA targets. Cell 120:15–20. doi:10.1016/j.cell.2004.12.035
51. Friedman RC, Farh KK, Burge CB, David P Bartel (2009) Most mammalian mRNAs are conserved targets of MicroRNAs. Genome Res 19:92–105. doi:10.1101/gr.082701.108
52. Grimson A, Farh KK, Johnston WK, Garrett-Engele P, Lim LP, Bartel DP (2007) MicroRNA targeting specificity in mammals: determinants beyond seed pairing. Mol Cell 27:91–105. doi:10.1016/j.molcel.2007.06.017
53. García DM, Baek D, Shin C, Bell GW, Grimson A, Bartel DP (2011) Weak seed-pairing stability and high target-site abundance decrease the proficiency of lsy-6 and other miRNAs. Nat Struct Mol Biol 18:1139–1146. doi:10.1038/nsmb.2115
54. Krüger, Rehmsmeier M (2006) RNAhybrid: microRNA target prediction easy, fast and flexible. Nucleic Acids Res 34:W451–W454. doi:10.1093/nar/gkl243
55. Enright AJ, John B, Gaul U, Tuschl T, Sander C, Marks DS (2003) MicroRNA targets in drosophila. Genome Biol 5:R1. doi:10.1186/gb-2003-5-1-r1
56. Johnes-Rahoades MW, Bartel DP (2004) Computational identification of plant microRNAsand their targets, inducing a stress-induced miRNA. Mol Cell 14:787–799. doi:10.1016/j.molcel.2004.05.027
57. Adai A, Cameron J, Sizolwenkosi M, Sarah A, Varun M, Vicki V, Venkatesan S (2005) Computational prediction of miRNAs in Arabidopsis thaliana. Genome Res 15:78–91. doi:10.1101/gr.2908205
58. Grün D, Wang YL, Langenberger D, Gunsalus KC, Rajewsky N (2005) microRNA target predictions across seven drosophila species and comparison to mammalian targets. PLoS Comput Biol 1:e13. doi:10.1371/journal.pcbi.0010013
59. Anders G, Mackowiak SD, Jens M, Maaskola J, Kuntzagk A, Rajewsky N et al (2012) doRiNA: a database of RNA interactions in post-transcriptional regulation. Nucleic Acids Res 40:D180–D186. doi:10.1093/nar/gkr1007
60. Krek A, Grun D, Poy M, Wolf R, Rosenberg L et al (2005) Combinatorial microRNA target predictions. Nat Genet 37:495–500. doi:10.1038/ng1536
61. Miranda KC, Huynh T, Tay Y, Ang YS, Tam WL et al (2006) A pattern-based method for the identification of MicroRNA binding sites and their corresponding heteroduplexes. Cell 126:1203–1217. doi:10.1016/j.cell.2006.07.031
62. Kertesz M, Iovino N, Unnerstall U, Gaul U, Segal E (2007) The role of site accessibility in microRNA target recognition. Nat Genet 39:1278–1284. doi:10.1038/ng2135
63. Gaidatzis D, Van Nimwegen E, Hausser J, Zavolan M (2007) Inference of miRNA targets using evolutionary conservation and pathway analysis. BMC Bioinformatics 8:69. doi:10.1186/1471-2105-8-69
64. Maragkakis M, Reczko M, Simossis VA, Alexiou P P, Papadopoulos GL et al (2009) DIANA-microT web server: elucidating microRNA functions through target prediction. Nucleic Acids Res 37:W273–W276. doi:10.1093/nar/gkp292
65. RusINov V, Baev V, Minkov IN, Tabler M (2005) MicroInspector: a web tool for detection of miRNA binding sites in an RNA sequence. Nucleic Acids Res 33:W696–W700. doi:10.1093/nar/gki364
66. Stark A, Brennecke J, Bushati N, Russell RB, Cohen SM (2005) Animal MicroRNAs confer robustness to gene expression and have a significant impact on 3′UTR evolution. Cell 123:1133–1146. doi:10.1016/j.cell.2005.11.023
67. Hammell M, Dang L, Zhang L, Lee A, Carmack CS et al (2008) mirWIP: microRNA target prediction based on microRNA-containing ribonucleoprotein–enriched transcripts. Nat methods 5:813–819. doi:10.1038/nmeth.1247
68. Hsu JB, Chiu CM, Hsu SD, Huang WY, Chien CH, Lee TY, Huang HD (2011) miRTar: an integrated system for identifying miRNA-target interactions in human. BMC Bioinform 12:300. doi:10.1186/1471-2105-12-300
69. Saetrom O, Snove O Jr, Saetrom P (2005) Weighted sequence motifs as an improved seeding step in microRNA target prediction algorithms. RNA 11:995–1003. doi:10.1261/rna.7290705
70. Huang JC, Babak T, Corson TW, Chua G, Khan S et al (2007) Using expression profiling data to identify human microRNA, targets. Nat Methods 4:1045–1049. doi:10.1038/nmeth1130
71. Kim SK, Nam JW, Rhee JK, Lee WJ, Zhang BT (2006) miTarget: microRNA target gene prediction using a support vector machine. BMC Bioinform 7:411. doi:10.1186/1471-2105-7-411
72. Sturm M, Hackenberg M, Langenberger D, Frishman D (2010) TargetSpy: a supervised machine learning approach for microRNA target prediction. BMC Bioinform 11:292. doi:10.1186/1471-2105-11-292
73. Bandyopadhyay S, Mitra R (2009) TargetMiner: microRNA target prediction with systematic identification of tissue-specific negative examples. Bioinformatics 25:2625–2631. doi:10.1093/bioinformatics/btp503
74. Yang Y, Wang YP, Li KB (2008) MiRTif: a support vector machine-based microRNA target interaction filter. BMC Bioinform 9:S4. doi:10.1186/1471-2105-9-S12-S4
75. Yan X, Chao T, Tu K, Zhang Y, Xie Lu, Gong Y, Yuan J, Qiang B, Peng X (2007) Improving the prediction of human microRNA target genes by using ensemble algorithm. FEBS Lett 581:1587–1593. doi:10.1016/j.febslet.2007.03.022
76. Wang X, El Naqa IM (2008) Prediction of both conserved and nonconserved microRNA targets in animals. Bioinformatics 24:325–332. doi:10.1093/bioinformatics/btm595
77. Chandra V, devi GR, Nair AS, Pillai SS, Pillai RM (2010) MTar: a computational microRNA target prediction architecture for human transcriptome. BMC Bioinform 11:S2. doi:10.1186/1471-2105-11-S1-S2
78. Betel D, Koppal A, Agius P, Sander C, Leslie C (2010) Comprehensive modeling of microRNA targets predicts functional non-conserved and non-canonical sites. Genome Biol 11:R90. doi:10.1186/gb-2010-11-8-r90
79. Friedman Y, Karsenty S, Linial M (2014) miRror-Suite: decoding coordinated regulation by microRNAs. Database(Oxford): bau043 doi:10.1093/database/bau043
80. Friedman I, Naamati G, Linial M (2010) MiRror: a combinatorial analysis web tool for ensembles of microRNAs and their targets. Bioinformatics 26(15):1920–1921. doi:10.1093/bioinformatics/btq298
81. Reyes-Herrera PH, Ficarra E, Acquaviva A, Macii E (2011) miREE: miRNA recognition elements ensemble. BMC Bioinform 12:454. doi:10.1186/1471-2105-12-454
82. Vergoulis T, Vlachos IS, Alexiou P, Georgakilas G et al (2012) Tarbase 6.0: capturing the exponential growth of miRNA targets with experimental support. Nucleic Acids Res 40:D222–D229. doi:10.1093/nar/gkr1161
83. Papadopoulos GL, Reczko M, Simossis VA, Sethupathy P, Hatzigeorgiou AG (2009) The database of experimentally supported targets: a functional update of TarBase. Nucleic Acids Res 37:D155–D158. doi:10.1093/nar/gkn809
84. Sethupathy P, Corda B, Hatzigeorgiou AG (2006) TarBase: a comprehensive database of experimentally supported animal microRNA targets. RNA 12:192–197. doi:10.1261/rna.2239606
85. LeeYJ, Kim V, Muth DC, Witwer KW (2015) Validated MicroRNA target databases: an evaluation. Drug Dev Res 76: 389–396. doi:10.1002/ddr.21278.
86. Xiao F, Zuo Z, Cai G, Kang S, Gao X, Li T (2009) miRecords: an integrated resource for microRNA–target interactions. Nucleic Acids Res 37:D105–D110. doi:10.1093/nar/gkn851
87. Nam S, Kim B, Shin S, Lee S (2008) miRGator: an integrated system for functional annotation of microRNAs. Nucleic Acids Res 36(Database issue):D159–D164. doi:10.1093/nar/gkm829
88. Cho S, Jun Y, Lee S, Choi HS, Jung S, Jang Y, Park C, Kim S, Lee S, Kim W (2011) miRGator v2.0: an integrated system for functional investigation of microRNAs. Nucleic Acids Res 39(Database issue):D158–D162. doi:10.1093/nar/gkq1094
89. Cho S, Jang I, Jun Y, Yoon S et al (2013) miRGator v3.0: a microRNA portal for deep sequencing, expression profiling, and mRNA targeting. Nucleic Acids Res 41(Database issue):D252–D257. doi:10.1093/nar/gks1168
90. Dweep H, Sticht C, Pandey P, Gretz N (2011) miRWalk—database: prediction of possible miRNA binding sites by “walking” the genes of three genomes. J Biomed Inform 44:839–847. doi:10.1016/j.jbi.2011.05.002
91. Hsu SD, Lin FM, Wu WY, Liang C, Huang WC, Chan WL, Tsai WT et al (2011) miRTarBase: a database curates experimentally validated microRNA—target interactions. Nucleic Acids Res 39:D163–D169. doi:10.1093/nar/gkq1107
92. Hsu SD, Tseng YT, Shrestha S, Lin YL, Khaleel A, Chou CH, Chu CF et al (2014) miRTarBase update 2014: an information resource for experimentally validated miRNA-target interactions. Nucleic Acids Res 42:D78–D85. doi:10.1093/nar/gkt1266
93. Naeem H, Kuffner R, Csaba G, Zimmer R (2010) miRSel: automated extraction of associations between microRNAs and genes from the biomedical literature. BMC Bioinformatics 11:135. doi:10.1186/1471-2105-11-135
94. Yang JH, Li, JH Shao P, Zhou H, Chen YQ, Qu LH (2011) starBase: a database for exploring microRNA–mRNA interaction maps from Argonaute CLIP-Seq and Degradome-Seq data. Nucleic Acids Res 39:D202–D209. doi:10.1093/nar/gkq1056
95. Li JH, Liu S, Zhou H, Qu LH, Yang JH (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–D97. doi:10.1093/nar/gkt1248
96. Sun X, Dong B, Yin L, Zhang R, Du W, Liu D et al (2013) PMTED: a plant microRNA target expression database. BMC Bioinform 14:174. doi:10.1093/nar/gkq1107
97. Pio G, Ceci M, Malerba D, D Elia D (2015) ComiRNet: a web-based system for the analysis of miRNA-gene regulatory networks. BMC Bioinform 16:S7. doi:10.1186/1471-2105-16-S9-S7
98. Pio G, Ceci M, D’Elia D, Malerba D (2014) Integrating microRNA target predictions for the discovery of gene regulatory networks: a semi-supervised ensemble learning approach. BMC Bioinform 15:S4. doi:10.1186/1471-2105-15-S1-S4
99. Pio G, Ceci M, D’Elia D, Loglisci C, Malerba D (2013) A novel biclustering algorithm for the discovery of meaningful biological correlations between miRNAs and mRNAs. BMC Bioinform 14:S8. doi:10.1186/1471-2105-14-S7-S8
100. Pio G, Ceci M, D’Elia D, Loglisci C, Malerba D (2013) HOCCLUS2: a biclustering algorithm for the discovery of miRNA:mRNA regulatory modules. Italian Symposium on Advanced Database Systems (SEBD)
101. Pio G, Ceci M, D’Elia D, Loglisci C, Malerba D 2012 Hierarchical and Overlapping Co-Clustering of mRNA:miRNA. Interactions European Conference on Artificial Intelligence (ECAI)
102. Pio G, Ceci M, D’Elia D, Malerba D (2014) Network reconstruction for the identification of miRNA:mRNA interaction networks. Machine Learning and Knowledge Discovery in Databases, ECML-PKDD-LNCS 8726:pp 508–511.
103. Guo ZW, Xie C, Yang JR, Li JH, Yang JH, Zheng L (2015) MtiBase: a database for decoding microRNA target sites located within CDS and 5′UTR regions from CLIP-Seq and expression profile datasets. Database: (Journal of Biological Databases Curation) 2015:bav102. doi:10.1093/database/bav102
104. Wang X (2008) miRDB: a microRNA target prediction and functional annotation database with a wiki interface. RNA 14:1012–1017. doi:10.1261/rna.965408
105. Betel D, Wilson M, Gabow A, Marks DS, Sander C (2008) The microRNA.org resource: targets and expression. Nucleic Acids Res 36:D149–D153. doi:10.1093/nar/gkm995
106. Betel D, Koppal A, Agius P, Sander C, Leslie C (2010) mirSVR predicted target site scoring method: comprehensive modeling of microRNA targets predicts functional non-conserved and non-canonical sites. Genome Biol 11:R90. doi:10.1186/gb-2010-11-8-r90
107. Gennarino VA, Sardiello M, Mutarelli M, Dharmalingam G, Maselli V et al (2011) HOCTAR database: a unique resource for microRNA target prediction. Gene 480:51–58. doi:10.1016/j.gene.2011.03.005
108. Gennarino VA, Sardiello M, Avellino R, Meola N, Maselli V, Anand S, Cutillo L, Ballabio A, Banfi S (2008) MicroRNA target prediction by expression analysis of host genes. Genome Res 19:481–490; Published in Advance December 16, 2008. doi:10.1101/gr.084129.108.
109. Elefant N, Berger A, Shein H, Hofree M, Margalit H, Altuvia Y (2011) RepTar: a database of predicted cellular targets of host and viral miRNAs. Nucleic Acids Res 39:D188–D194. doi:10.1093/nar/gkq1233
110. Piriyapongsa J, Bootchai C, Ngamphiw C, Tongsima S (2012) microPIR: an integrated database of MicroRNA target sites within human promoter sequences. PLoS One 7:e33888. doi:10.1371/journal.pone.0033888
111. Kumar A, Wong AK, Tizard ML, Moore RJ, Lefèvre C (2012) miRNA_targets: a database for miRNA target predictions in coding and non-coding regions of mRNAs. Genomics 100:352–356. doi:10.1016/j.ygeno.2012.08.006
112. Rukov JL, Wilentzik R, Jaffe I, Vinther J, Shomron N (2013) Pharmaco-miR: linking microRNAs and drug effects. Brief Bioinform 15:648–659. doi:10.1093/bib/bbs082
113. Ru Y, Kechris KJ, Tabakoff B, Hoffman P, Radcliffe RA, Bowler B et al (2014) The multiMiR R package and database: integration of microRNA–target interactions along with their disease and drug associations. Nucleic Acids Res 42:e133. doi:10.1093/nar/gku631
114. Wang J, Lu M, Qiu C, Cui Q (2010) TransmiR: a transcription factor–microRNA regulation database. Nucleic Acids Res (2010) 38: D119–D122. doi:10.1093/nar/gkp803.
115. Bandyopadhyay S, Bhattacharyya M (2010) PuTmiR: a database for extracting neighboring transcription factors of human microRNAs. BMC Bioinform 11:190. doi:10.1186/1471-2105-11-190
116. Bruno AE, Li L, Kalabus JL, Pan Y, Yu A, Hu Z (2012) miRdSNP: a database of disease-associated SNPs and microRNA target sites on 3′UTRs of human genes. BMC Genomics 13:44. doi:10.1186/1471-2164-13-44
117. Bao L, Zhou M, Wu L, Lu L, Goldowitz D, Williams RW, Cui Y (2007) PolymiRTS Database: linking polymorphisms in microRNA target sites with complex traits. Nucleic Acids Res. 35: D51–D54. doi:10.1093/nar/gkl797
118. Ziebarth JD, Bhattacharya A, Chen A, Cui Y (2012) PolymiRTS Database 2.0: linking polymorphisms in microRNA target sites with human diseases and complex traits. Nucleic Acids Res 40:D216–D221. doi:10.1093/nar/gkr1026
119. Bhattacharya A, Ziebarth JD, Cui Y (2014) PolymiRTS Database 3.0: linking polymorphisms in microRNAs and their target sites with human diseases and biological pathways. Nucleic Acids Res 42:D86–D91. doi:10.1093/nar/gkt1028
120. Laganà A, Paone A, Veneziano D, Cascione L, Gasparini P et al (2012) miR-EdiTar: A database of predicted A-to-I edited miRNA target sites. Bioinformatics 28:3166–3168. doi:10.1093/bioinformatics/bts589
121. Hsu PW, Lin LZ, Hsu SD, Hsu JB, Huang HD (2007) ViTa: prediction of host microRNAs targets on viruses. Nucleic Acids Res 35:D381–D385. doi:10.1093/nar/gkl1009
122. Li SC, Shiau CK, Lin WC (2008) Vir-Mir db: prediction of viral microRNA candidate hairpins. Nucleic Acids Res 36:D184–D189. doi:10.1093/nar/gkm610
123. Li SC, Pan CY, Lin WC (2006) Bioinformatic discovery of microRNA precursors from human ESTs and introns. BMC Genomics 7(1):164. doi:10.1186/1471-2164-7-164