Research interests


RNA COMPUTATIONAL BIOLOGY (non-coding RNAs)


The objective of these work is the development of methods and softwares to solve problems of identification and characterization of non-coding RNAs (ncRNAs). Especifically, these work focuses on the structural analysis of secondary structure of the RNAs, prediction and annotation of sequences of RNAs and in the development of new mechanisms of ncRNA characterization.


PATTERN RECOGNITION APPLIED TO SYSTEM BIOLOGY


The objective of these work to model biological systems, particularlly gene networks. Our main aim is to develop and use new pattern recognition approaches on Gene Networks Inference from expression data, specially through the data integration of biological information like protein-protein interactions, celular process, gene funcionl, methabolic pathways, celular localization and network topology.


COMPUTER VISION: PROCESSING AND IMAGE ANALYSIS


This line of research proposes the research, development and validation methods and pattern recognition techniques such as selection / extraction characteristics, dimensionality reduction, etc., which are applied in processing and image analysis, recovery images based on content and the development of classifiers.

NEURAL NETOWRKS (DEEP LEARING)


PROBABILISTICS METHODS


ARTIFICIAL INTELLIGENCE


BIOLOGICAL DATA SCIENCE


EVOLUTIONARY ALGORITHMS


DATA MINING


INFORMATION THEORY


COMPLEX NETOWRKS


DATABASES AND DATA INTEGRATION


BIOMEDICAL AND AGRICULTURE APPLICATIONS