Who we are
Welcome to the webpage of the Human Systems Biology group in the National Institute for Genomic Medicine at Mexico City, INMEGEN. Our group is interdisciplinary and have the objective to develop a systems biology framework to analyze mainly human diseases and metabolic phenotype in microorganisms through the use of computational models and high-throughput technologies. Currently, our laboratory focuses on the analysis of metabolic alterations in cancer cells by the implementation of genome scale metabolic reconstructions and assess the predictions in terms of experimental data at different scales.
Latest News
Biological Physics Mexico City 2019
from 06-09-2019 to 04-09-2019
Frontier Science at the Intersection of Physics, Math and Biology The BioPhys Mexico City 2019 conference, the third in a biennial series, is intended as an international, multidisciplinary scientific forum to discuss the latest developments in biological physics, including experimental, theoretical and computational methods, from a single molecule perspective to complex multi-component environments. The conference is expected to boost the new paradigm of interdisciplinary approaches converging into specific problems in biological physics.
Latest Publication
Exploring metabolic anomalies in COVID-19 and post-COVID-19: a machine learning approach with explainable artificial intelligence
Frontiers in Molecular Biosciences 2024
Juan José Oropeza-Valdez, Cristian Padron-Manrique, Aarón Vázquez-Jiménez, Xavier Soberón and Osbaldo Resendis-Antonio
The COVID-19 pandemic, caused by SARS-CoV-2, has led to significant challenges worldwide, including diverse clinical outcomes and prolonged post-recovery symptoms known as Long COVID or Post-COVID-19 syndrome. Emerging evidence suggests a crucial role of metabolic reprogramming in the infection’s long-term consequences. This study employs a novel approach utilizing machine learning (ML) and explainable artificial intelligence (XAI) to analyze metabolic alterations in COVID-19 and Post-COVID-19 patients. Samples were taken from a cohort of 142 COVID-19, 48 Post-COVID-19, and 38 control patients, comprising 111 identified metabolites.