Evidence map›Paper›PMID 26361499›Full record

ArticleBMC proceedings2015

PathwayMatrix: visualizing binary relationships between proteins in biological pathways.

Tuan Nhon Dang, Paul Murray, Angus Graeme Forbes

Abstract read
In one paragraph

Article in BMC proceedings, 2015. 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

3 authors.

Tuan Nhon DangDepartment of Computer Science M/C 152, University of Illinois at Chicago, 851 S. Morgan, Room 1120, Chicago 60607-7053, IL, USA.
Paul MurrayDepartment of Computer Science M/C 152, University of Illinois at Chicago, 851 S. Morgan, Room 1120, Chicago 60607-7053, IL, USA.
Angus Graeme ForbesDepartment of Computer Science M/C 152, University of Illinois at Chicago, 851 S. Morgan, Room 1120, Chicago 60607-7053, IL, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMolecular activation pathways are inherently complex, and understanding relations across many biochemical reactions and reaction types is difficult. Visualizing and analyzing a pathway is a challenge due to the network size and the diversity of relations between proteins and molecules.

resultsIn this paper, we introduce PathwayMatrix, a visualization tool that presents the binary relations between proteins in the pathway via the use of an interactive adjacency matrix. We provide filtering, lensing, clustering, and brushing and linking capabilities in order to present relevant details about proteins within a pathway.

conclusionsWe evaluated PathwayMatrix by conducting a series of in-depth interviews with domain experts who provided positive feedback, leading us to believe that our visualization technique could be helpful for the larger community of researchers utilizing pathway visualizations. PathwayMatrix is freely available at https://github.com/CreativeCodingLab/PathwayMatrix.

Indexed as

Binary RelationshipsBiological networksMatrix visualizationPathway visualization

Identifiers

PMID26361499
PMCPMC4547148

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

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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.