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Osbaldo Resendis-Antonio

Researcher at National Autonomous University of Mexico

Publications -  55
Citations -  1558

Osbaldo Resendis-Antonio is an academic researcher from National Autonomous University of Mexico. The author has contributed to research in topics: Medicine & Biology. The author has an hindex of 17, co-authored 43 publications receiving 1114 citations. Previous affiliations of Osbaldo Resendis-Antonio include University of California, San Diego.

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MEMOTE for standardized genome-scale metabolic model testing

Christian Lieven, +84 more
- 01 Mar 2020 - 
TL;DR: A community effort to develop a test suite named MEMOTE (for metabolic model tests) to assess GEM quality, and advocate adoption of the latest version of the Systems Biology Markup Language level 3 flux balance constraints (SBML3FBC) package as the primary description and exchange format.
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Regulation by transcription factors in bacteria: beyond description

TL;DR: This review transmits the main ideas or concepts behind regulation by transcription factors and gives just enough examples to sustain these main ideas, thus avoiding a classical ennumeration of facts.
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MICOM: Metagenome-Scale Modeling To Infer Metabolic Interactions in the Gut Microbiota.

TL;DR: In this article, a customizable metabolic model of the human gut microbiome is presented, based on a heuristic optimization approach based on L2 regularization, which is able to obtain a unique set of realistic growth rates that corresponded well with observed replication rates.
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Modular analysis of the transcriptional regulatory network of E. coli

TL;DR: These modules were identified by a clustering approach, using the shortest path to trace regulatory relationships across genes in the network, and the type and distribution of motifs between and within modules supported the notion of a hierarchical network with defined functional modules.
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Metabolic Reconstruction and Modeling of Nitrogen Fixation in Rhizobium etli

TL;DR: Some evidence is presented supporting that FBA of the reconstructed metabolic network for R. etli provides results that are in agreement with physiological observations, and the reconstructed genome-scale metabolic network provides an important framework which allows us to compare model predictions with experimental measurements and eventually generate hypotheses on ways to improve nitrogen fixation.