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Knowledge Base Commons (KBCommons) v1.1: a universal framework for multi-omics data integration and biological discoveries
BACKGROUND: 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 develo...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6923931/ https://www.ncbi.nlm.nih.gov/pubmed/31856718 http://dx.doi.org/10.1186/s12864-019-6287-8 |
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author | Zeng, Shuai Lyu, Zhen Narisetti, Siva Ratna Kumari Xu, Dong Joshi, Trupti |
author_facet | Zeng, Shuai Lyu, Zhen Narisetti, Siva Ratna Kumari Xu, Dong Joshi, Trupti |
author_sort | Zeng, Shuai |
collection | PubMed |
description | BACKGROUND: 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. METHODS: KBCommons 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. RESULTS: KBCommons 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. CONCLUSIONS: KBCommons 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/. |
format | Online Article Text |
id | pubmed-6923931 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-69239312019-12-30 Knowledge Base Commons (KBCommons) v1.1: a universal framework for multi-omics data integration and biological discoveries Zeng, Shuai Lyu, Zhen Narisetti, Siva Ratna Kumari Xu, Dong Joshi, Trupti BMC Genomics Research BACKGROUND: 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. METHODS: KBCommons 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. RESULTS: KBCommons 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. CONCLUSIONS: KBCommons 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/. BioMed Central 2019-12-20 /pmc/articles/PMC6923931/ /pubmed/31856718 http://dx.doi.org/10.1186/s12864-019-6287-8 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Zeng, Shuai Lyu, Zhen Narisetti, Siva Ratna Kumari Xu, Dong Joshi, Trupti Knowledge Base Commons (KBCommons) v1.1: a universal framework for multi-omics data integration and biological discoveries |
title | Knowledge Base Commons (KBCommons) v1.1: a universal framework for multi-omics data integration and biological discoveries |
title_full | Knowledge Base Commons (KBCommons) v1.1: a universal framework for multi-omics data integration and biological discoveries |
title_fullStr | Knowledge Base Commons (KBCommons) v1.1: a universal framework for multi-omics data integration and biological discoveries |
title_full_unstemmed | Knowledge Base Commons (KBCommons) v1.1: a universal framework for multi-omics data integration and biological discoveries |
title_short | Knowledge Base Commons (KBCommons) v1.1: a universal framework for multi-omics data integration and biological discoveries |
title_sort | knowledge base commons (kbcommons) v1.1: a universal framework for multi-omics data integration and biological discoveries |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6923931/ https://www.ncbi.nlm.nih.gov/pubmed/31856718 http://dx.doi.org/10.1186/s12864-019-6287-8 |
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