RESENDIS ANTONIO LAB


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

Memote: A community driven effort towards a standardized genome-scale metabolic model test suite

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Several studies have shown that neither the formal representation nor the functional requirements of genome-scale metabolic models (GEMs) are precisely defined. Without a consistent standard, comparability, reproducibility, and interoperability of models across groups and software tools cannot be guaranteed. Here, we present memote (https://github.com/opencobra/memote) an open-source software containing a community-maintained, standardized set of metabolic model tests. The tests cover a range of aspects from annotations to conceptual integrity and can be extended to include experimental datasets for automatic model validation.

Latest Publication

Memote: A community driven effort towards a standardized genome-scale metabolic model test suite

Nature Biotechnology 2020

Christian Lieven, Moritz E. Beber, Brett G. Olivier, Frank T. Bergmann, Meric Ataman, Parizad Babaei, Jennifer A. Bartell, Lars M. Blank, Siddharth Chauhan, Kevin Correia, Christian Diener, Andreas Dräger, Birgitta E. Ebert, Janaka N. Edirisinghe, Jose P. Faria, Adam Feist, Georgios Fengos, Ronan M. T. Fleming, Beatriz García-Jiménez, Vassily Hatzimanikatis, Wout van Helvoirt, Christopher S. Henry, Henning Hermjakob, Markus J. Herrgård, Hyun Uk Kim, Zachary King, Jasper J. Koehorst, Steffen Klamt, Edda Klipp, Meiyappan Lakshmanan, Nicolas Le Novère, Dong-Yup Lee, Sang Yup Lee, Sunjae Lee, Nathan E. Lewis, Hongwu Ma, Daniel Machado, Radhakrishnan Mahadevan, Paulo Maia, Adil Mardinoglu, Gregory L. Medlock, Jonathan M. Monk, Jens Nielsen, Lars Keld Nielsen, Juan Nogales, Intawat Nookaew, Osbaldo Resendis-Antonio, Bernhard O. Palsson, Jason A. Papin, Kiran R. Patil, Mark Poolman, Nathan D. Price, Anne Richelle, Isabel Rocha, Benjamin J. Sanchez, Peter J. Schaap, Rahuman S. Malik Sheriff, Saeed Shoaie, Nikolaus Sonnenschein, Bas Teusink, Paulo Vilaça, Jon Olav Vik, Judith A. Wodke, Joana C. Xavier, Qianqian Yuan, Maksim Zakhartsev and Cheng Zhang

Several studies have shown that neither the formal representation nor the functional requirements of genome-scale metabolic models (GEMs) are precisely defined. Without a consistent standard, comparability, reproducibility, and interoperability of models across groups and software tools cannot be guaranteed. Here, we present memote (https://github.com/opencobra/memote) an open-source software containing a community-maintained, standardized set of metabolic model tests. The tests cover a range of aspects from annotations to conceptual integrity and can be extended to include experimental datasets for automatic model validation.