BIOINFORMATICS LABORATORY
ABOUT US
WELCOME TO LAI2B
The Laboratory of Artificial Intelligence applied to Bioinformatics (LAI2B) focuses on developing and applying artificial intelligence methods to deal with hard to solve problems in several areas. Our main application has been in bioinformatics during the last years, treating with the analysis of gene expression data, the 3D protein structure prediction problem, and phylogenetic inference. We strongly believe that collaboration with an interdisciplinary team is a must in this area. We have collaborated with researchers to analyse datasets related to cancer, the wine industry, and healthcare analysis, among others.
In short, we aim at working closely with biologists and biotechnologist to understand the problems and to produce meaningful results by creating advanced algorithms using artificial intelligence techniques. The goal is to uncover the information hidden in the datasets.
We believe that frontiers do not exist for science, so we promote collaboration at a national and international level. Currently, we collaborate with researchers from Brasil, France, Ecuador, and Australia. In Chile, we collaborate with researchers from Universidad Austral, Universidad Católica del Maule, and other university departments.
If you like our work, we invite you to write to us, and we would be happy to discuss it. Just email any of the faculty members.
PROJECTS
RECENT PROJECTS
STIC-AMSUD 21-STIC-02
AICaBI: Artificial Intelligence for Cancer Biomarkes Identification
(2021-2022)
Fondecyt Postdoc 3200598
Phenomenological Cerebral Autoregulation Modelling by Using Multi-Objective Optimisation Approaches
(2020-2021)
Fondecyt Postdoc 3190822
A new evolutionary optimisation approach to deal with the many-objective phylogenetic inference problem
(2019-2021)
RECENT NEWS
From the 25th-29th of September 2023 our partner, the SBCB Laboratory, will organize the 4th Escola Gaucha de Bioinformática, that will take place at Universidade Federal de Rio Grande do Sul.
On May 2023 the PhD students visited for two weeks the SBCB Laboratory and work with the colleagues there on the application of pipelines for the analysis of gene expression Data. This visit happened as part of the activities of the AICABI project.
We congratulate Dr Mario Inostroza-Ponta for the recent adjudication of the Fondecyt Project "A novel multiobjective strategy to identify significant groups of genes using high throughput data and biological knowledge" in the 2023 grant.
From the 25th-27th of July we participated on the Second Workshop AICABI, UFRGS, Brazil. Researchers and PhD students attended this event as part of the activities of the STIC-AMSUD Research Project.
On the 14th of October we will held an online workshop as part of the activities of the AICABI project. More information coming soon.
We are happy to announce that we got a STIC-AMSUD grant to help the collaboration with our colleagues in Brazil and France for two years. The project entitled "AICaBI: Artificial Intelligence for Cancer Biomarkes Identification", will be focussed on the analysis of gene expression cancer data.
PUBLICATIONS
LATEST PUBLICATIONS
Parraga-Alava, J. and Inostroza-Ponta, M. Influence of the go-based semantic similarity measures in multi-objective gene clustering algorithm performance, Journal of Bioinformatics and Computational Biology, Vol. 18, No. 6, 2020 doi.org/10.1142/S0219720020500389
Troncoso, N., Rojo-González, R. Villalobos-Cid, M., Vásquez, O. C, Chavez. H. Economic decision-making tool for distributed solar photovoltaic panels and storage: The case of Chile. Energy Procedia 159:388 - 393, March 2019. DOI: 10.1016/j.egypro.2018.12.071.
Master thesis - Metaheurística basada en el algoritmo NSGA-II para el problema de predicción de la estructura terciaria de proteínas. Aliaga, S. (2020)