ChemiRs: A web application for microRNAs and chemicals

BMC Bioinformatics

Volumn 17, Issue 1, 2016, Pages

  Su, Emily Chia Yu ^a   Chen, Yu Sing ^b   Tien, Yun Cheng ^b   Liu, Jeff ^c   Ho, Bing Ching ^d   Yu, Sung Liang ^d   Singh, Sher ^b  

^a TAIPEI MEDICAL UNIVERSITY   (Taiwan)

^b NATIONAL TAIWAN NORMAL UNIVERSITY   (Taiwan)

^c NATIONAL TAIWAN UNIVERSITY   (Taiwan)

^d NATIONAL TAIWAN UNIVERSITY   (Taiwan)

Author keywords

Chemical; Disease; Gene ontology; Genomics; MicroRNA

Indexed keywords

CHEMICAL ANALYSIS; CHEMICALS; DISEASES; GENES; INDICATORS (CHEMICAL); QUERY PROCESSING;

ASSOCIATION ANALYSIS; BIOMEDICAL LITERATURE; ENVIRONMENTAL CHEMICALS; GENE ONTOLOGY; GENOMICS; MEDICAL SUBJECT HEADINGS; MICRORNAS; USER FRIENDLY INTERFACE;

RNA;

MICRORNA;

ALGORITHM; BIOLOGY; CHEMISTRY; GENETIC DATABASE; GENETICS; HUMAN; INTERNET; MEDICAL SUBJECT HEADINGS; MEDLINE; PROCEDURES; SOFTWARE;

ALGORITHMS; COMPUTATIONAL BIOLOGY; DATABASES, GENETIC; HUMANS; INTERNET; MEDICAL SUBJECT HEADINGS; MICRORNAS; PUBMED; SOFTWARE;

EID: 85007421337     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/s12859-016-1002-0     Document Type: Article

References (32)

1. Yang Q, Qiu C, Yang J, Wu Q, Cui Q. miREnvironment database: providing a bridge for microRNAs, environmental factors and phenotypes. Bioinformatics. 2011;27(23):3329-30.
2. Singh S, Li SS. Phthalates: toxicogenomics and inferred human diseases. Genomics. 2011;97(3):148-57.
3. Latronico MV, Catalucci D, Condorelli G. MicroRNA and cardiac pathologies. Physiol Genomics. 2008;34(3):239-42.
4. Witkos TM, Koscianska E, Krzyzosiak WJ. Practical Aspects of microRNA Target Prediction. Curr Mol Med. 2011;11(2):93-109.
5. Megraw M, Sethupathy P, Corda B, Hatzigeorgiou AG. miRGen: a database for the study of animal microRNA genomic organization and function. Nucleic Acids Res. 2007;35(Database issue):D149-55.
6. Dweep H, Sticht C, Pandey P, Gretz N. miRWalk-database: prediction of possible miRNA binding sites by "walking" the genes of three genomes. J Biomed Inform. 2011;44(5):839-47.
7. Yang JH, Li JH, Shao P, Zhou H, Chen YQ, Qu LH. starBase: a database for exploring microRNA-mRNA interaction maps from Argonaute CLIP-Seq and Degradome-Seq data. Nucleic Acids Res. 2011;39(Database issue):D202-9.
8. Coronnello C, Benos PV. ComiR: Combinatorial microRNA target prediction tool. Nucleic Acids Res. 2013;41(Web Server issue):W159-64.
9. Ekimler S, Sahin K. Computational Methods for MicroRNA Target Prediction. Genes. 2014;5(3):671-83.
10. Davis AP, Grondin CJ, Lennon-Hopkins K, Saraceni-Richards C, Sciaky D, King BL, Wiegers TC, Mattingly CJ. The Comparative Toxicogenomics Database's 10th year anniversary: update 2015. Nucleic Acids Res. 2015;43(Database issue): D914-20.
11. Maragkakis M, Reczko M, Simossis VA, Alexiou P, Papadopoulos GL, Dalamagas T, Giannopoulos G, Goumas G, Koukis E, Kourtis K, et al. DIANA-microT web server: elucidating microRNA functions through target prediction. Nucleic Acids Res. 2009;37(Web Server issue):W273-6.
12. Maragkakis M, Vergoulis T, Alexiou P, Reczko M, Plomaritou K, Gousis M, Kourtis K, Koziris N, Dalamagas T, Hatzigeorgiou AG. DIANA-microT Web server upgrade supports Fly and Worm miRNA target prediction and bibliographic miRNA to disease association. Nucleic acids research. 2011; 39(Web Server issue):W145-8.
13. John B, Enright AJ, Aravin A, Tuschl T, Sander C, Marks DS. Human MicroRNA targets. PLoS Biol. 2004;2(11):e363.
14. Wang X. miRDB: a microRNA target prediction and functional annotation database with a wiki interface. RNA. 2008;14(6):1012-7.
15. Kruger J, Rehmsmeier M. RNAhybrid: microRNA target prediction easy, fast and flexible. Nucleic Acids Res. 2006;34(Web Server issue):W451-4.
16. Krek A, Grun D, Poy MN, Wolf R, Rosenberg L, Epstein EJ, MacMenamin P, da Piedade I, Gunsalus KC, Stoffel M, et al. Combinatorial microRNA target predictions. Nat Genet. 2005;37(5):495-500.
17. Kertesz M, Iovino N, Unnerstall U, Gaul U, Segal E. The role of site accessibility in microRNA target recognition. Nat Genet. 2007;39(10):1278-84.
18. Miranda KC, Huynh T, Tay Y, Ang YS, Tam WL, Thomson AM, Lim B, Rigoutsos I. A pattern-based method for the identification of MicroRNA binding sites and their corresponding heteroduplexes. Cell. 2006;126(6): 1203-17.
19. Lewis BP, Burge CB, Bartel DP. Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets. Cell. 2005;120(1):15-20.
20. Xiao F, Zuo Z, Cai G, Kang S, Gao X, Li T. miRecords: an integrated resource for microRNA-target interactions. Nucleic Acids Res. 2009;37(Database issue): D105-10.
21. Jiang Q, Wang Y, Hao Y, Juan L, Teng M, Zhang X, Li M, Wang G, Liu Y. miR2Disease: a manually curated database for microRNA deregulation in human disease. Nucleic Acids Res. 2009;37(Database issue):D98-104.
22. Griffiths-Jones S, Saini HK, van Dongen S, Enright AJ. miRBase: tools for microRNA genomics. Nucleic Acids Res. 2008;36(Database issue):D154-8.
23. Kozomara A, Griffiths-Jones S. miRBase: integrating microRNA annotation and deep-sequencing data. Nucleic Acids Res. 2011;39(Database issue): D152-7.
24. Chou CH, Chang NW, Shrestha S, Hsu SD, Lin YL, Lee WH, Yang CD, Hong HC, Wei TY, Tu SJ, et al. miRTarBase 2016: updates to the experimentally validated miRNA-target interactions database. Nucleic Acids Res. 2016;44(D1):D239-47.
25. Kanehisa M, Goto S, Sato Y, Kawashima M, Furumichi M, Tanabe M. Data, information, knowledge and principle: back to metabolism in KEGG. Nucleic Acids Res. 2014;42(Database issue):D199-205.
26. Croft D, Mundo AF, Haw R, Milacic M, Weiser J, Wu G, Caudy M, Garapati P, Gillespie M, Kamdar MR, et al. The Reactome pathway knowledgebase. Nucleic Acids Res. 2014;42(Database issue):D472-7.
27. Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, Davis AP, Dolinski K, Dwight SS, Eppig JT, et al. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet. 2000;25(1):25-9.
28. Li Y, Liu H, Lai C, Du X, Su Z, Gao S. The Lin28/let-7a/c-Myc pathway plays a role in non-muscle invasive bladder cancer. Cell Tissue Res. 2013;354(2):533-41.
29. NaciffJM, Khambatta ZS, Reichling TD, Carr GJ, Tiesman JP, Singleton DW, Khan SA, Daston GP. The genomic response of Ishikawa cells to bisphenol A exposure is dose-and time-dependent. Toxicology. 2010;270(2-3):137-49.
30. Setiawan VW, Monroe KR, Wilkens LR, Kolonel LN, Pike MC, Henderson BE. Breast cancer risk factors defined by estrogen and progesterone receptor status: the multiethnic cohort study. Am J Epidemiol. 2009;169(10):1251-9.
31. Bhan A, Hussain I, Ansari KI, Bobzean SA, Perrotti LI, Mandal SS. Bisphenol-A and diethylstilbestrol exposure induces the expression of breast cancer associated long noncoding RNA HOTAIR in vitro and in vivo. J Steroid Biochem Mol Biol. 2014;141:160-70.
32. Holmes AK, Koller KR, Kieszak SM, Sjodin A, Calafat AM, Sacco FD, Varner DW, Lanier AP, Rubin CH. Case-control study of breast cancer and exposure to synthetic environmental chemicals among Alaska Native women. Int J Circumpolar Health. 2014;73:25760.