miRNAfe: A comprehensive tool for feature extraction in microRNA prediction.
miRNAfe is a comprehensive tool to extract features from RNA sequences. It is freely available as a web service, allowing a single access point to almost all state-of-the-art feature extraction methods used today in a variety of works from different authors. It has a very simple user interface, where the user only needs to load a file containing the input sequences and select the features to extract. As a result, the user obtains a text file with the features extracted, which can be used to analyze the sequences or as input to a miRNA prediction software. The tool can calculate up to 80 features where many of them are multidimensional arrays. In order to simplify the web interface, the features have been divided into six pre-defined groups, each one providing information about: primary sequence, secondary structure, thermodynamic stability, statistical stability, conservation between genomes of different species and substrings analysis of the sequences. Additionally, pre-trained classifiers are provided for prediction in different species. All algorithms to extract the features have been validated, comparing the results with the ones obtained from software of the original authors. The source code is freely available for academic use under GPL license at http://sourceforge.net/projects/sourcesinc/files/mirnafe/0.90/. A user-friendly access is provided as web interface at http://fich.unl.edu.ar/sinc/web-demo/mirnafe/. A more configurable web interface can be accessed at http://fich.unl.edu.ar/sinc/web-demo/mirnafe-full/.
Research Center for Signals, Systems and Computational Intelligence, sinc(i), FICH-UNL, CONICET, Ciudad Universitaria UNL, 3000 Santa Fe, Argentina. Electronic address: cyones@sinc.unl.edu.ar.
Cristian A
CA
Yones
Research Center for Signals, Systems and Computational Intelligence, sinc(i), FICH-UNL, CONICET, Ciudad Universitaria UNL, 3000 Santa Fe, Argentina.
Georgina
G
Stegmayer
Instituto de Investigaciones en Microbiología y Parasitología Médica (UBA), CONICET, Paraguay 2155, piso 13, 1121, Buenos Aires, Argentina.
Laura
L
Kamenetzky
Research Center for Signals, Systems and Computational Intelligence, sinc(i), FICH-UNL, CONICET, Ciudad Universitaria UNL, 3000 Santa Fe, Argentina.
Diego H
DH
Milone
D000465:Algorithms; D000818:Animals; D001483:Base Sequence; D006801:Humans; D035683:MicroRNAs / Q000235:genetics*; D008969:Molecular Sequence Data; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D016415:Sequence Alignment / Q000379:methods*; D017423:Sequence Analysis, RNA / Q000379:methods*; D012984:Software; D012985:Software Design
D035683:MicroRNAs
Feature extraction; MicroRNA; Web tool