Evidence map›Paper›PMID 30135734›Full record

ArticleF1000Research2018

Epiviz Web Components: reusable and extensible component library to visualize functional genomic datasets.

Jayaram Kancherla, Alexander Zhang, Brian Gottfried, Hector Corrada Bravo

Abstract read
In one paragraph

Article in F1000Research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

4 authors.

Jayaram KancherlaCenter for Bioinformatics and Computational Biology, University of Maryland, College Park, College Park, Maryland, 20742, USA.ORCID 0000-0001-5855-5031
Alexander ZhangDepartment of Computer Science, University of Maryland, College Park, College Park, Maryland, 20742, USA.
Brian GottfriedDepartment of Computer Science, University of Maryland, College Park, College Park, Maryland, 20742, USA.
Hector Corrada BravoCenter for Bioinformatics and Computational Biology, University of Maryland, College Park, College Park, Maryland, 20742, USA.

Funding

Integrative Visual and Computational Exploratory Analysis of Genomics DataR01GM114267 · NIGMS · UNIV OF MARYLAND, COLLEGE PARK · PI CORRADA BRAVO, HECTOR · 2015 to 2018
$1.8M
NIGMS NIH HHS R01 GM114267
6 · The paper itself

Abstract

Interactive and integrative data visualization tools and libraries are integral to exploration and analysis of genomic data. Web based genome browsers allow integrative data exploration of a large number of data sets for a specific region in the genome. Currently available web-based genome browsers are developed for specific use cases and datasets, therefore integration and extensibility of the visualizations and the underlying libraries from these tools is a challenging task. Genomic data visualization and software libraries that enable bioinformatic researchers and developers to implement customized genomic data viewers and data analyses for their application are much needed. Using recent advances in core web platform APIs and technologies including Web Components, we developed the Epiviz Component Library, a reusable and extensible data visualization library and application framework for genomic data. Epiviz Components can be integrated with most JavaScript libraries and frameworks designed for HTML. To demonstrate the ease of integration with other frameworks, we developed an R/Bioconductor

Indexed as

Computer GraphicsDatabases, Nucleic AcidGenomicsSoftwareWeb Browserbioinformaticsepigeneticsgenomicsvisualizationweb components

Identifiers

PMID30135734
PMCPMC6092909

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.