The analysis of biological data aims at helping medical practitioners to better understand the biological processes that happen in several situations like diseases, treatment, environmental conditions, time, among others. In this project we aim at developing and applying metaheuristics, machine learning techniques and ad-hoc computational strategies to integrate and analyse omic data for the identification of novel biomarkers for diagnostic and prognostic. Base on bioinformatic approach, we specifically aim at looking at cancer data, involving the participation of researchers from Computer Science and Biology and Medicine background. The main contributions of this project are: publication of scientific articles, scientific dissemination through lectures, papers presented in congresses, meetings and workshops; development and availability of online tools containing project results; training of postgraduate students; development of tools for the scientific community: technical reports, libraries, methodologies and tools developed will be made available to the scientific community. Also it is expected the preparation, submission and approval of projects for additional research funding to foster the cooperation between these research groups.
AICaBI: Artificial Intelligence for Cancer Biomarkes Identification
Estado:
En ejecución
Investigador responsable
Co - Investigador
Tipo de Proyecto
STIC2020025
Área
Bioinformática