Abstract
BackgroundKnowledge Base Commons (KBCommons) v1.1 is a universal and all-inclusive web-based framework providing generic functionalities for storing, sharing, analyzing, exploring, integrating and visualizing multiple organisms’ genomics and integrative omics data. KBCommons is designed and developed to integrate diverse multi-level omics data and to support biological discoveries for all species via a common platform.MethodsKBCommons has four modules including data storage, data processing, data accessing, and web interface for data management and retrieval. It provides a comprehensive framework for new plant-specific, animal-specific, virus-specific, bacteria-specific or human disease-specific knowledge base (KB) creation, for adding new genome versions and additional multi-omics data to existing KBs, and for exploring existing datasets within current KBs.ResultsKBCommons has an array of tools for data visualization and data analytics such as multiple gene/metabolite search, gene family/Pfam/Panther function annotation search, miRNA/metabolite/trait/SNP search, differential gene expression analysis, and bulk data download capacity. It contains a highly reliable data privilege management system to make users’ data publicly available easily and to share private or pre-publication data with members in their collaborative groups safely and securely. It allows users to conduct data analysis using our in-house developed workflow functionalities that are linked to XSEDE high performance computing resources. Using KBCommons’ intuitive web interface, users can easily retrieve genomic data, multi-omics data and analysis results from workflow according to their requirements and interests.ConclusionsKBCommons addresses the needs of many diverse research communities to have a comprehensive multi-level OMICS web resource for data retrieval, sharing, analysis and visualization. KBCommons can be publicly accessed through a dedicated link for all organisms at http://kbcommons.org/.
Highlights
Introduction to methodology and encoding rulesJ Chem Inf Comput Sci. 1988;28(1):31–6. 37
Users can bring in their private dataset for any organism and visualize any public or sharable dataset via KBCommons interface
Contribute to MaizeKB and retrieve data With differential expression dataset generated by Cuffdiff, we show an example of contribution of multiomics data to existing knowledge base (KB)
Summary
Introduction to methodology and encoding rulesJ Chem Inf Comput Sci. 1988;28(1):31–6. 37. Knowledge Base Commons (KBCommons) v1.1 is a universal and all-inclusive web-based framework providing generic functionalities for storing, sharing, analyzing, exploring, integrating and visualizing multiple organisms’ genomics and integrative omics data. KBCommons is designed and developed to integrate diverse multi-level omics data and to support biological discoveries for all species via a common platform. Zeng et al BMC Genomics 2019, 20(Suppl 11):947 research It plays a role in central data repository aggregating soybean multi-omics data, and contains various bioinformatics tools for data analysis and visualization. It is publicly available at http://soykb.org, and has wide range of usage around the world, with more than 500 registered users. Providing a comprehensive and flexible framework which are more customized and developed to support cross-species translational research is a need
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