Blending Biology and Computation to understand human diseases.

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

MicroRNAs Regulate Metabolic Phenotypes During Multicellular Tumor Spheroids Progression

Frontiers in Oncology 2020

Erick Andrés Muciño-Olmos, Aarón Vázquez-Jiménez, Diana Elena López-Esparza, Vilma Maldonado, Mahara Valverde and Osbaldo Resendis-Antonio

During tumor progression, cancer cells ire their metabolism to face their bioenergetic demands. In recent years, microRNAs (miRNAs) have emerged as regulatory elements that inhibit the translation and stability of crucial mRNAs, some of them causing direct metabolic alterations in cancer. In this study, we investigated the relationship between miRNAs and their targets mRNAs that control metabolism, and how this fine-tuned regulation is diversified depending on the tumor stage. To do so, we implemented a paired analysis of RNA-seq and small RNA-seq in a breast cancer cell line (MCF7).