Author

Álvaro Gargantilla-Becerra

Consejo Superior de Investigaciones CientíficasORCID 0000-0003-0429-2365Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 2 Organism:bacteria (other)· 1 Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1 Approach:machine learning (classical)· 1 Assay:metagenomics· 1 Approach:statistical model· 1

Frequent Co-Authors

Juan NogalesiD· 2 shared

Activity by Year

2025-2026 · peak 1/yr

2 papers

Recent·Most cited

BioinformaticsbioRxivPreprintSep 16, 2026

ML4SD: Leveraging Machine Learning and High-Throughput Search Algorithms for an Iterative Growth-Coupled Design Innovation

Álvaro Gargantilla-Becerra, Juan Nogales

ML4SD improves microbial biomanufacturing by combining active learning and high-throughput search to optimize growth-coupled production with fewer design iterations.

DOI 10.64898/2026.09.11.750664

machine learning (classical)benchmarking

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BioinformaticsbioRxivPreprintDec 12, 2025

EMBER: A Genome-Scale Approach for a Systematic Characterization of Bacterial Metabolic Heterogeneity through the Growth-Adaptation Trade-Off

Álvaro Gargantilla-Becerra, Juan Nogales

EMBER identifies adaptive metabolic reactions in bacteria by integrating transcriptomics and flux analysis, revealing differences in resource allocation strategies across species.

1 citation

bacteria (other)metagenomics

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