GAUGE-Annotated Microbial Transcriptomic Data Facilitate Parallel Mining and High-Throughput Reanalysis To Form Data-Driven Hypotheses
Zhongyou Li, Katja Koeppen, Victoria Holden, Samuel L. Neff, Liviu Cengher, Elora G. Demers, Dallas L. Mould, Bruce A. Stanton, Thomas H. Hampton
Abstract
GEO archives transcriptomic data from over 5,800 microbial experiments and allows researchers to answer questions not directly addressed in published papers. However, less than 4% of the microbial data sets include the sample group annotations required for high-throughput reanalysis.
Topics & Concepts
AnnotationTranscriptomeWorkflowData miningGene AnnotationSample (material)Computer scienceComputational biologyGauge (firearms)BiologyInformation retrievalBioinformaticsGeneDatabaseGene expressionGeneticsGeographyPhysicsThermodynamicsGenomeArchaeologyGenomics and Phylogenetic StudiesBiomedical Text Mining and OntologiesMicrobial Community Ecology and Physiology