RegulonDB has been the main resource for knowledge about transcriptional regulation and organization in E. coli K-12, and has been accessed intensively since its first publication in 1998 (PMID: 9399800). For instance, in the last four years, RegulonDB was accessed an average of ~16,300 times per year, and citations to RegulonDB articles quickly count in the hundreds. This curated database started more than 20 years ago, before the advent of high-throughput (HT) experimentation, gathering data obtained by traditional methods, with some HT data added later on. Here we present a major undertaking in ensuring high coverage of the latest HT experimental data in RegulonDB, by incorporating more than 500 HT datasets for transcription factor (TF) DNA-binding, in addition to 1,864 RNA-seq datasets generated under different growth conditions and/or genetic backgrounds. Another novelty in this BioResource is the curation effort to associate each dataset with its corresponding detailed metadata that is key for its utilization. The value of having the derived genomic features, or objects, from different kinds of experiments, available in a single repository, will add to the already acknowledged value of RegulonDB to the scientific community.
(from the RegulonDB 11.0 article)
Programs used to generate uniform collections of HT objects, mapping them to low-throughput (LT) data, and a manual describing the associated processes and formats.
See also the . From Zenodo, the users can find a link to this docker container with the dataset collections in MongoDB, the web services in GraphQL, and the web interface in React.
[How the first task can be performed with the software, or, in the more extensive documentation, a link to the quick start. Outlines how to quickly get started with the software using a basic yet practical example]
[If the software does make high demand on particular resources, then this should be clearly advertised and explained.]
[Defines the set of rules and conditions for people who want to use the software.]
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