Evidence map›Paper›PMID 36610985›Full record

ArticleBioinformatics (Oxford, England)2023

Vaa3D-x for cross-platform teravoxel-scale immersive exploration of multidimensional image data.

Jiangshan Liang, Luchen Deng, Shize Chen, Yimin Wang, Zongcai Ruan, Lingli Zhang

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
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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

6 authors.

Jiangshan LiangSchool of Computer Science and Engineering, Southeast University, Nanjing, Jiangsu, China.
Luchen DengSchool of Computer Science and Engineering, Southeast University, Nanjing, Jiangsu, China.
Shize ChenSchool of Computer Science and Engineering, Southeast University, Nanjing, Jiangsu, China.
Yimin WangGuangdong Institute of Intelligence Science and Technology, Hengqin, Guangdong, China.
Zongcai RuanSchool of Computer Science and Engineering, Southeast University, Nanjing, Jiangsu, China.
Lingli ZhangSchool of Biological Science and Medical Engineering, Southeast University, Nanjing, Jiangsu, China.ORCID 0000-0002-8685-3578

Funding

National Science and Technology Innovation 2030
6 · The paper itself

Abstract

summaryVaa3D is a software package that has been widely used to visualize and analyze multidimensional microscopic images in a number of cutting edge bioimage informatics applications. However, due to many recent updates of both software development environments and operating systems, it was highly requested to maintain Vaa3D and disseminate it on latest operating systems. In addition, there has never been a showcase about how to use Vaa3D's cross-platform visualization and immersive exploration functions for multidimensional and teravoxel-scale images. Here, we introduce a newly developed version of the software, called Vaa3D-x, to address all the above issues. AVAILABILITY AND IMPLEMENTATION: Vaa3D-x is released in both binary and Open-Source available at vaa3d.org and GitHub (https://github.com/Vaa3D). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Indexed as

Computational BiologyImage Processing, Computer-AssistedSoftwareMicroscopy

Identifiers

PMID36610985
PMCPMC9832945

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.