Development of “KBCommons” — universal informatics framework for multi-omics translational research

Abstract

Multi-level 'OMICS' data integration for multiple organisms has been one of the major challenges in the era of advanced next generation sequencing and high performance technologies. However, these data are often stored individually across different web resources based on data type and organism making it difficult to find and integrate them. There are many websites which stores different data types and display data in pie charts or plain text format but limit their data to only one fixed organism. Making it difficult for researchers working on other biological organisms including plants, animals, humans, and microbes have similar needs with multi-level omics data. These complex omics data requires extensive data management, exhaustive computational analysis, and effective integration to have a one-stop interactive, web-based portal to browse, access, analyze, integrate, visualize and share knowledge about genomics and molecular mechanisms, with ultimate links to phenotypes and traits. To achieve this, we have developed Knowledge Base Commons (KBCommons), a platform that automates the process of establishing the database and making the tools for organisms available via a dedicated web resource.