Evidence map›Paper›PMID 36215728›Full record

ArticleJournal of integrative bioinformatics2022

Towards a hybrid user interface for the visual exploration of large biomolecular networks using virtual reality.

Michael Aichem, Karsten Klein, Tobias Czauderna, Dimitar Garkov, Jinxin Zhao, Jian Li, Falk Schreiber

Abstract read
In one paragraph

Article in Journal of integrative bioinformatics, 2022. 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

7 authors.

Michael AichemDepartment of Computer and Information Science, University of Konstanz, Konstanz, Germany.
Karsten KleinDepartment of Computer and Information Science, University of Konstanz, Konstanz, Germany.
Tobias CzaudernaFaculty of Applied Computer Sciences & Biosciences, University of Applied Sciences Mittweida, Mittweida, Germany.ORCID https://orcid.org/0000-0002-1788-9593
Dimitar GarkovDepartment of Computer and Information Science, University of Konstanz, Konstanz, Germany.ORCID https://orcid.org/0000-0002-2134-1686
Jinxin ZhaoInfection Program and Department of Microbiology, Biomedicine Discovery Institute, Monash University, Melbourne, Australia.
Jian LiInfection Program and Department of Microbiology, Biomedicine Discovery Institute, Monash University, Melbourne, Australia.
Falk SchreiberDepartment of Computer and Information Science, University of Konstanz, Konstanz, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Biomolecular networks, including genome-scale metabolic models (GSMMs), assemble the knowledge regarding the biological processes that happen inside specific organisms in a way that allows for analysis, simulation, and exploration. With the increasing availability of genome annotations and the development of powerful reconstruction tools, biomolecular networks continue to grow ever larger. While visual exploration can facilitate the understanding of such networks, the network sizes represent a major challenge for current visualisation systems. Building on promising results from the area of immersive analytics, which among others deals with the potential of immersive visualisation for data analysis, we present a concept for a hybrid user interface that combines a classical desktop environment with a virtual reality environment for the visual exploration of large biomolecular networks and corresponding data. We present system requirements and design considerations, describe a resulting concept, an envisioned technical realisation, and a systems biology usage scenario. Finally, we discuss remaining challenges.

Indexed as

User-Computer InterfaceVirtual RealityComputer Simulationhybrid user interfacesimmersive analyticsmetabolic network modelssystems biologyvirtual reality

Identifiers

PMID36215728
PMCPMC9800044

What OpenQuestion holds

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LicenceCC BY
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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.