A Scalable Genetic Programming Approach to Integrate miRNA-Target Predictions: Comparing Different Parallel Implementations of M3GP
Joint Authors
Milanesi, Luciano
Castelli, Mauro
Trujillo, Leonardo
Popovič, Aleš
Beretta, Stefano
Muñoz, Luis
Martínez, Yuliana
Merelli, Ivan
Source
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-07-04
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
There are many molecular biology approaches to the analysis of microRNA (miRNA) and target interactions, but the experiments are complex and expensive.
For this reason, in silico computational approaches able to model these molecular interactions are highly desirable.
Although several computational methods have been developed for predicting the interactions between miRNA and target genes, there are substantial differences in the results achieved since most algorithms provide a large number of false positives.
Accordingly, machine learning approaches are widely used to integrate predictions obtained from different tools.
In this work, we adopt a method called multidimensional multiclass GP with multidimensional populations (M3GP), which relies on a genetic programming approach, to integrate and classify results from different miRNA-target prediction tools.
The results are compared with those obtained with other classifiers, showing competitive accuracy.
Since we aim to provide genome-wide predictions with M3GP and, considering the high number of miRNA-target interactions to test (also in different species), a parallel implementation of this algorithm is recommended.
In this paper, we discuss the theoretical aspects of this algorithm and propose three different parallel implementations.
We show that M3GP is highly parallelizable, it can be used to achieve genome-wide predictions, and its adoption provides great advantages when handling big datasets.
American Psychological Association (APA)
Beretta, Stefano& Castelli, Mauro& Muñoz, Luis& Trujillo, Leonardo& Martínez, Yuliana& Popovič, Aleš…[et al.]. 2018. A Scalable Genetic Programming Approach to Integrate miRNA-Target Predictions: Comparing Different Parallel Implementations of M3GP. Complexity،Vol. 2018, no. 2018, pp.1-13.
https://search.emarefa.net/detail/BIM-1134452
Modern Language Association (MLA)
Beretta, Stefano…[et al.]. A Scalable Genetic Programming Approach to Integrate miRNA-Target Predictions: Comparing Different Parallel Implementations of M3GP. Complexity No. 2018 (2018), pp.1-13.
https://search.emarefa.net/detail/BIM-1134452
American Medical Association (AMA)
Beretta, Stefano& Castelli, Mauro& Muñoz, Luis& Trujillo, Leonardo& Martínez, Yuliana& Popovič, Aleš…[et al.]. A Scalable Genetic Programming Approach to Integrate miRNA-Target Predictions: Comparing Different Parallel Implementations of M3GP. Complexity. 2018. Vol. 2018, no. 2018, pp.1-13.
https://search.emarefa.net/detail/BIM-1134452
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1134452