Comparing Deep and Machine Learning Approaches in Bioinformatics: A miRNA-Target Prediction Case Study

Valentina Giansanti, Mauro Castelli, Stefano Beretta, Ivan Merelli

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)


MicroRNAs (miRNAs) are small non-coding RNAs with a key role in the post-transcriptional gene expression regularization, thanks to their ability to link with the target mRNA through the complementary base pairing mechanism. Given their role, it is important to identify their targets and, to this purpose, different tools were proposed to solve this problem. However, their results can be very different, so the community is now moving toward the deployment of integration tools, which should be able to perform better than the single ones. As Machine and Deep Learning algorithms are now in their popular years, we developed different classifiers from both areas to verify their ability to recognize possible miRNA-mRNA interactions and evaluated their performance, showing the potentialities and the limits that those algorithms have in this field. Here, we apply two deep learning classifiers and three different machine learning models to two different miRNA-mRNA datasets, of predictions from 3 different tools: TargetScan, miRanda, and RNAhybrid. Although an experimental validation of the results is needed to better confirm the predictions, deep learning techniques achieved the best performance when the evaluation scores are taken into account.

Original languageEnglish
Title of host publicationComputational Science – ICCS 2019
Subtitle of host publication19th International Conference, Faro, Portugal, June 12–14, 2019, Proceedings, Part III
EditorsValeria V. Krzhizhanovskaya, Michael H. Lees, Peter M.A. Sloot, Jack J. Dongarra, João M.F. Rodrigues, Pedro J.S. Cardoso, Jânio Monteiro, Roberto Lam
PublisherSpringer Verlag
Number of pages14
ISBN (Print)9783030227432
Publication statusPublished - 1 Jan 2019
Event19th International Conference on Computational Science, ICCS 2019 - Faro, Portugal
Duration: 12 Jun 201914 Jun 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11538 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference19th International Conference on Computational Science, ICCS 2019


  • Deep learning
  • Machine learning
  • miRNA
  • miRNA-target prediction


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