MirMark: a Site-level and UTR-level Classifier for MiRNA Target Prediction

Overview

Journal Genome Biol

Specialties Biology
Genetics

Date 2014 Oct 26

PMID 25344330

Citations 20

Authors

Mark Menor

Travers Ching

Xun Zhu

David Garmire

Lana X Garmire

Affiliations

Soon will be listed here.

Abstract

MiRNAs play important roles in many diseases including cancers. However computational prediction of miRNA target genes is challenging and the accuracies of existing methods remain poor. We report mirMark, a new machine learning-based method of miRNA target prediction at the site and UTR levels. This method uses experimentally verified miRNA targets from miRecords and mirTarBase as training sets and considers over 700 features. By combining Correlation-based Feature Selection with a variety of statistical or machine learning methods for the site- and UTR-level classifiers, mirMark significantly improves the overall predictive performance compared to existing publicly available methods. MirMark is available from https://github.com/lanagarmire/MirMark.

Citing Articles

microT-CNN: an avant-garde deep convolutional neural network unravels functional miRNA targets beyond canonical sites.

Zacharopoulou E, Paraskevopoulou M, Tastsoglou S, Alexiou A, Karavangeli A, Pierros V Brief Bioinform. 2024; 26(1).

PMID: 39737571 PMC: 11685103. DOI: 10.1093/bib/bbae678.

AEmiGAP: AutoEncoder-Based miRNA-Gene Association Prediction Using Deep Learning Method.

Yoon S, Yoon H, Cho J, Lee K Int J Mol Sci. 2024; 25(23).

PMID: 39684787 PMC: 11641653. DOI: 10.3390/ijms252313075.

The Evolution of Nucleic Acid-Based Diagnosis Methods from the (pre-)CRISPR to CRISPR era and the Associated Machine/Deep Learning Approaches in Relevant RNA Design.

Chakraborty S, Ray Dutta J, Ganesan R, Minary P Methods Mol Biol. 2024; 2847:241-300.

PMID: 39312149 DOI: 10.1007/978-1-0716-4079-1_17.

Benchmarking the negatives: Effect of negative data generation on the classification of miRNA-mRNA interactions.

Cohen-Davidi E, Veksler-Lublinsky I PLoS Comput Biol. 2024; 20(8):e1012385.

PMID: 39186797 PMC: 11379385. DOI: 10.1371/journal.pcbi.1012385.

GraphTar: applying word2vec and graph neural networks to miRNA target prediction.

Przybyszewski J, Malawski M, Licholai S BMC Bioinformatics. 2023; 24(1):436.

PMID: 37978418 PMC: 10657114. DOI: 10.1186/s12859-023-05564-x.

References

Maragkakis M, Alexiou P, Papadopoulos G, Reczko M, Dalamagas T, Giannopoulos G . Accurate microRNA target prediction correlates with protein repression levels. BMC Bioinformatics. 2009; 10:295. PMC: 2752464. DOI: 10.1186/1471-2105-10-295. View

Hunten S, Siemens H, Kaller M, Hermeking H . The p53/microRNA network in cancer: experimental and bioinformatics approaches. Adv Exp Med Biol. 2013; 774:77-101. DOI: 10.1007/978-94-007-5590-1_5. View

Kishore S, Jaskiewicz L, Burger L, Hausser J, Khorshid M, Zavolan M . A quantitative analysis of CLIP methods for identifying binding sites of RNA-binding proteins. Nat Methods. 2011; 8(7):559-64. DOI: 10.1038/nmeth.1608. View

Ritchie W, Flamant S, Rasko J . mimiRNA: a microRNA expression profiler and classification resource designed to identify functional correlations between microRNAs and their targets. Bioinformatics. 2009; 26(2):223-7. DOI: 10.1093/bioinformatics/btp649. View

Marin R, Voellmy F, von Erlach T, Vanicek J . Analysis of the accessibility of CLIP bound sites reveals that nucleation of the miRNA:mRNA pairing occurs preferentially at the 3'-end of the seed match. RNA. 2012; 18(10):1760-70. PMC: 3446701. DOI: 10.1261/rna.033282.112. View

Shin C, Nam J, Farh K, Chiang H, Shkumatava A, Bartel D . Expanding the microRNA targeting code: functional sites with centered pairing. Mol Cell. 2010; 38(6):789-802. PMC: 2942757. DOI: 10.1016/j.molcel.2010.06.005. View

Hata A . Functions of microRNAs in cardiovascular biology and disease. Annu Rev Physiol. 2012; 75:69-93. PMC: 5215839. DOI: 10.1146/annurev-physiol-030212-183737. View

Hafner M, Landthaler M, Burger L, Khorshid M, Hausser J, Berninger P . Transcriptome-wide identification of RNA-binding protein and microRNA target sites by PAR-CLIP. Cell. 2010; 141(1):129-41. PMC: 2861495. DOI: 10.1016/j.cell.2010.03.009. View

Wang K, Garmire L, Young A, Nguyen P, Trinh A, Subramaniam S . Role of microRNA-23b in flow-regulation of Rb phosphorylation and endothelial cell growth. Proc Natl Acad Sci U S A. 2010; 107(7):3234-9. PMC: 2840325. DOI: 10.1073/pnas.0914825107. View

10.

Reczko M, Maragkakis M, Alexiou P, Papadopoulos G, Hatzigeorgiou A . Accurate microRNA Target Prediction Using Detailed Binding Site Accessibility and Machine Learning on Proteomics Data. Front Genet. 2012; 2:103. PMC: 3265086. DOI: 10.3389/fgene.2011.00103. View

11.

Witkos T, Koscianska E, Krzyzosiak W . Practical Aspects of microRNA Target Prediction. Curr Mol Med. 2011; 11(2):93-109. PMC: 3182075. DOI: 10.2174/156652411794859250. View

12.

Thomas M, Lieberman J, Lal A . Desperately seeking microRNA targets. Nat Struct Mol Biol. 2010; 17(10):1169-74. DOI: 10.1038/nsmb.1921. View

13.

Peng H, Long F, Ding C . Feature selection based on mutual information: criteria of max-dependency, max-relevance, and min-redundancy. IEEE Trans Pattern Anal Mach Intell. 2005; 27(8):1226-38. DOI: 10.1109/TPAMI.2005.159. View

14.

Sun K, Chen X, Jiang P, Song X, Wang H, Sun H . iSeeRNA: identification of long intergenic non-coding RNA transcripts from transcriptome sequencing data. BMC Genomics. 2013; 14 Suppl 2:S7. PMC: 3582448. DOI: 10.1186/1471-2164-14-S2-S7. View

15.

Yue D, Liu H, Huang Y . Survey of Computational Algorithms for MicroRNA Target Prediction. Curr Genomics. 2010; 10(7):478-92. PMC: 2808675. DOI: 10.2174/138920209789208219. View

16.

Lorenz R, Bernhart S, Honer Zu Siederdissen C, Tafer H, Flamm C, Stadler P . ViennaRNA Package 2.0. Algorithms Mol Biol. 2011; 6:26. PMC: 3319429. DOI: 10.1186/1748-7188-6-26. View

17.

Friedman R, Farh K, Burge C, Bartel D . Most mammalian mRNAs are conserved targets of microRNAs. Genome Res. 2008; 19(1):92-105. PMC: 2612969. DOI: 10.1101/gr.082701.108. View

18.

John B, Enright A, Aravin A, Tuschl T, Sander C, Marks D . Human MicroRNA targets. PLoS Biol. 2004; 2(11):e363. PMC: 521178. DOI: 10.1371/journal.pbio.0020363. View

19.

Vergoulis T, Vlachos I, Alexiou P, Georgakilas G, Maragkakis M, Reczko M . TarBase 6.0: capturing the exponential growth of miRNA targets with experimental support. Nucleic Acids Res. 2011; 40(Database issue):D222-9. PMC: 3245116. DOI: 10.1093/nar/gkr1161. View

20.

Wilbert M, Yeo G . Genome-wide approaches in the study of microRNA biology. Wiley Interdiscip Rev Syst Biol Med. 2011; 3(5):491-512. PMC: 3482411. DOI: 10.1002/wsbm.128. View