Evidence map›Paper›PMID 30767777›Full record

ArticleBMC bioinformatics2019

BioVR: a platform for virtual reality assisted biological data integration and visualization.

Jimmy F Zhang, Alex R Paciorkowski, Paul A Craig, Feng Cui

Abstract read
In one paragraph

Article in BMC bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

  1. Review
  2. Article
  3. Advances in laboratory medicine · 2024
    Article
  4. Applications of the metaverse in medicine and healthcare.Advances in laboratory medicine · 2024
    Review
  5. Article
  6. Review
  7. Metaverse Wearables for Immersive Digital Healthcare: A Review.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023
    Review
  8. Extended reality for biomedicine.Nature reviews. Methods primers · 2023
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Review
  18. 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.

Jimmy F ZhangThomas H. Gosnell School of Life Sciences, Rochester Institute of Technology, One Lomb Memorial Drive, Rochester, NY, 14623, USA. jfz8009@rit.edu.
Alex R PaciorkowskiDepartments of Neurology, Pediatrics, Biomedical Genetics, and Neuroscience, University of Rochester Medical Center, 601 Elmwood Ave, Rochester, NY, 14642, USA.
Paul A CraigSchool of Chemistry and Materials Science, Rochester Institute of Technology, One Lomb Memorial Drive, Rochester, NY, 14623, USA.
Feng CuiThomas H. Gosnell School of Life Sciences, Rochester Institute of Technology, One Lomb Memorial Drive, Rochester, NY, 14623, USA. fxcsbi@rit.edu.ORCID http://orcid.org/0000-0002-5186-5720

Funding

Uncovering a new role of nucleosomes in gene regulationR15GM116102 · NIGMS · ROCHESTER INSTITUTE OF TECHNOLOGY · PI CUI, FENG · 2015 to 2019
$883k
Biology of developmental encephalopathies presenting with infantile spasmsK08NS078054 · NINDS · UNIVERSITY OF ROCHESTER · PI PACIORKOWSKI, ALEXANDER R · 2013 to 2017
$779k
National Institute of General Medical Sciences R15GM116102National Institute of Neurological Disorders and Stroke K08NS078054NIGMS NIH HHS R15 GM116102NINDS NIH HHS K08 NS078054
6 · The paper itself

Abstract

backgroundFunctional characterization of single nucleotide variants (SNVs) involves two steps, the first step is to convert DNA to protein and the second step is to visualize protein sequences with their structures. As massively parallel sequencing has emerged as a leading technology in genomics, resulting in a significant increase in data volume, direct visualization of SNVs together with associated protein sequences/structures in a new user interface (UI) would be a more effective way to assess their potential effects on protein function.

resultsWe have developed BioVR, an easy-to-use interactive, virtual reality (VR)-assisted platform for integrated visual analysis of DNA/RNA/protein sequences and protein structures using Unity3D and the C# programming language. It utilizes the cutting-edge Oculus Rift, and Leap Motion hand detection, resulting in intuitive navigation and exploration of various types of biological data. Using Gria2 and its associated gene product as an example, we present this proof-of-concept software to integrate protein and nucleic acid data. For any amino acid or nucleotide of interest in the Gria2 sequence, it can be quickly linked to its corresponding location on Gria2 protein structure and visualized within VR.

conclusionsUsing innovative 3D techniques, we provide a VR-based platform for visualization of DNA/RNA sequences and protein structures in aggregate, which can be extended to view omics data.

Indexed as

Models, BiologicalSoftwareVirtual RealityComputer GraphicsDNAHumansProtein ConformationProteinsRNAUser-Computer InterfaceDNAProteinsRNAData visualizationGRIA2User InterfaceVirtual reality

Identifiers

PMID30767777
PMCPMC6376704

What OpenQuestion holds

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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.