A convolutional deep residual neural network for prediction of pre-miRNAs in genome-wide data.
PhDSeeker is a bio-inspired algorithm for synthesizing linear and branched metabolic pathways.
A blind, single channel dereverberation method in the time-frequency domain.
Semi-supervised method for microRNA prediction with few labelled samples.
Arousal and valence are estimated from features of heart rate variability.
Compares a supervised vs an unsupervised approach for pre-miRNA prediction in model genomes.
A novel method to smoothly control the diversity of a cluster ensemble.
Algorithm for frequency-domain blind source separation based on Multibin ICA for 2 by 2 mixtures.
Algorithm for frequency-domain blind source separation based on the pseudoanechoic model.
miRNAfe full is an advanced tool to extract features from RNA sequences, providing almost all state-of-the-art feature extraction methods published today.
A deep learning approach for the automatic interpretation of scientific articles.
Clustermatch is an efficient clustering method able to process highly diverse datasest.
A regularity-based algorithm designed for long-term analysis of foraging behavior in grazing cattle.
Extreme learning machines for reverse engineering of gene regulatory networks from expression time series.
Blind speech dereverberation based on convolutive non-negative matrix factorization with mixed penalization.
Classification of Furnariidae species using speech-related features and machine learning.
A novel and effective way of approaching high class-imbalance in pre-miRNA prediction.
A novel method for inferring biological function for a set of genes with previously unknown function.
miRNA-SOM is a tool for the discovery of pre-miRNA in the E. multilocularis genome.
An evolutionary tool for finding novel metabolic pathways linking compounds through feasible reactions.
A comprehensive tool providing almost all state-of-the-art RNA feature extraction methods used today.