Mining all publicly available expression data to compute dynamic microbial transcriptional regulatory networks
説明
<jats:title>Abstract</jats:title><jats:p>We are firmly in the era of biological big data. Millions of omics datasets are publicly accessible and can be employed to support scientific research or build a holistic view of an organism. Here, we introduce a workflow that converts all public gene expression data for a microbe into a dynamic representation of the organism’s transcriptional regulatory network. This five-step process walks researchers through the mining, processing, curation, analysis, and characterization of all available expression data, using<jats:italic>Bacillus subtilis</jats:italic>as an example. The resulting reconstruction of the<jats:italic>B. subtilis</jats:italic>regulatory network can be leveraged to predict new regulons and analyze datasets in the context of all published data. The results are hosted at<jats:ext-link xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="uri" xlink:href="https://imodulondb.org/">https://imodulondb.org/</jats:ext-link>, and additional analyses can be performed using the PyModulon Python package. As the number of publicly available datasets increases, this pipeline will be applicable to a wide range of microbial pathogens and cell factories.</jats:p>