Evidence map›Paper›PMID 31856718›Full record

ArticleBMC genomics2019

Knowledge Base Commons (KBCommons) v1.1: a universal framework for multi-omics data integration and biological discoveries.

Shuai Zeng, Zhen Lyu, Siva Ratna Kumari Narisetti, Dong Xu, Trupti Joshi

Abstract read
In one paragraph

Article in BMC genomics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Shuai ZengDepartment of Electrical Engineering and Computer Science, University of Missouri-Columbia, Columbia, MO, USA.
Zhen LyuDepartment of Electrical Engineering and Computer Science, University of Missouri-Columbia, Columbia, MO, USA.
Siva Ratna Kumari NarisettiDepartment of Electrical Engineering and Computer Science, University of Missouri-Columbia, Columbia, MO, USA.
Dong XuDepartment of Electrical Engineering and Computer Science, University of Missouri-Columbia, Columbia, MO, USA.
Trupti JoshiChristopher S. Bond Life Sciences Center, University of Missouri-Columbia, Columbia, MO, USA. joshitr@health.missouri.edu.

Funding

WU INSTITUTE OF CLINICAL AND TRANSLATIONAL SCIENCESUL1TR002345 · NCATS · WASHINGTON UNIVERSITY · PI William G. Powderly · 2017 to 2026
$97.8M
NCATS NIH HHS UL1 TR002345
6 · The paper itself

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/.

Indexed as

Databases, GeneticKnowledge BasesAnimalsComputational BiologyDatabase Management SystemsGenomeHumansInformation Storage and RetrievalInternetWorkflowGenomicsKnowledge BaseMulti-omics dataOrganism-specific databaseVisualization and analysis

Identifiers

PMID31856718
PMCPMC6923931

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.