The application of high-throughput technologies in projects of life sciences generate exponential amounts of data, so that their nature and complexity inspired the development of new computational methods for the extraction and management of relevant biological information in order to achieve a more complete understanding of life, both at molecular and population levels. This technological context defines a new multidisciplinary field of research known as Bioinformatics.
In the group we are interested in the development of algorithms and bioinformatics tools for the analysis, processing and managing of spectroscopy data, microarrays, molecular markers and high-throughput sequencing projects in the framework of basic and multidisciplinary biological research.
Our work also in Bioinformatics also inspires the introduction of high-throughput technologies and data processing in Precision Agriculture in the context of the emerging research field known as Agroinformatics.
Design of multiclass classifiers based in error correcting codes for the analysis of biological data (data with noise and /or high dimensionality).
Design of algorithms of automatic variable selection in biological data using measure sets (fuzzy integrals).
Tests, adaptation and development of tools for the analysis of biological data of various types (sequences, expression, markers, spectroscopy) with emphasis in the use of machine learning techniques.
Design of database in functional genomics projects.
Design of DNA bar codes by means of error correcting codes.
Precision Agriculture - Agroinformatics
Development of ISOBUS technologies (hardware and software) for mass sensing of variables of agronomic interest.
Dr. Elizabeth Tapia
Investigate in Design of multiclass classifiers for processing microarray data using error correction codes. Stability of variable selection methods. Design of DNA barcodes based on error correction codes.