ShinyOmics: collaborative exploration of omics-data
新经济:经济学数据的协同探索
作者: Defne SurujonTim van Opijnen
作者单位: 1Biology Department, Boston College, 02467, Chestnut Hill, MA, USA
刊名: BMC Bioinformatics, 2020, Vol.21 (2), pp.613-619
来源数据库: Springer Nature Journal
DOI: 10.1186/s12859-020-3360-x
关键词: Systems biologyVisualizationTranscriptomicsFunctional genomicsData integration
英文摘要: Abstract(#br)Background(#br)Omics-profiling is a collection of increasingly prominent approaches that result in large-scale biological datasets, for instance capturing an organism’s behavior and response in an environment. It can be daunting to manually analyze and interpret such large datasets without some programming experience. Additionally, with increasing amounts of data; management, storage and sharing challenges arise. Results(#br)Here, we present ShinyOmics, a web-based application that allows rapid collaborative exploration of omics-data. By using Tn-Seq, RNA-Seq, microarray and proteomics datasets from two human pathogens, we exemplify several conclusions that can be drawn from a rich dataset. We identify a protease and several chaperone proteins upregulated under aminoglycoside...
全文获取路径: Springer Nature  (合作)
分享到:
来源刊物:
影响因子:3.024 (2012)

×