Author: Kevin Rychel

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Preprints

Machine-learning from Pseudomonas putida transcriptomes reveals its transcriptional regulatory network

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Mining all publicly available expression data to compute dynamic microbial transcriptional regulatory networks

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Machine learning uncovers independently regulated modules in the Bacillus subtilis transcriptome

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Machine learning of all Mycobacterium Tuberculosis H37Rv RNA-seq data reveals complex interplay between metabolism, stress response, and infection

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Machine Learning of Pseudomonas aeruginosa transcriptomes identifies independently modulated sets of genes associated with known transcriptional regulators

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iModulonDB: a knowledgebase of microbial transcriptional regulation derived from machine learning

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Pan-genomic analysis of transcriptional modules across Salmonella Typhimurium reveals the regulatory landscape of different strains

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Machine learning uncovers a data-driven transcriptional regulatory network for the Crenarchaeal thermoacidophile Sulfolobus acidocaldarius

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Advanced transcriptomic analysis reveals the role of efflux pumps and media composition in antibiotic responses of Pseudomonas aeruginosa

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