Evidence map›Paper›PMID 28929969›Full record

ArticleBMC bioinformatics2017

CellNetVis: a web tool for visualization of biological networks using force-directed layout constrained by cellular components.

Henry Heberle, Marcelo Falsarella Carazzolle, Guilherme P Telles, Gabriela Vaz Meirelles, Rosane Minghim

Abstract read
In one paragraph

Article in BMC bioinformatics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Article
  6. Article
  7. SPV: a JavaScript Signaling Pathway Visualizer.Bioinformatics (Oxford, England) · 2018
    Article
  8. 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

5 authors.

Henry HeberleUniversity of São Paulo, Instituto de Ciências Matemáticas e de Computação, Av. Trabalhador São-carlense, 400, São Carlos-SP, Brazil.
Marcelo Falsarella CarazzolleUniversity of Campinas, Institute of Biology, Av. Albert Einstein, 1251, Campinas-SP, Brazil.
Guilherme P TellesUniversity of Campinas, Institute of Computing, Av. Albert Einstein, 1251, Campinas-SP, Brazil.
Gabriela Vaz MeirellesBiosciences National Laboratory, Caixa Postal 6192, Campinas-SP, Brazil.
Rosane MinghimUniversity of São Paulo, Instituto de Ciências Matemáticas e de Computação, Av. Trabalhador São-carlense, 400, São Carlos-SP, Brazil. rminghim@icmc.usp.br.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe advent of "omics" science has brought new perspectives in contemporary biology through the high-throughput analyses of molecular interactions, providing new clues in protein/gene function and in the organization of biological pathways. Biomolecular interaction networks, or graphs, are simple abstract representations where the components of a cell (e.g. proteins, metabolites etc.) are represented by nodes and their interactions are represented by edges. An appropriate visualization of data is crucial for understanding such networks, since pathways are related to functions that occur in specific regions of the cell. The force-directed layout is an important and widely used technique to draw networks according to their topologies. Placing the networks into cellular compartments helps to quickly identify where network elements are located and, more specifically, concentrated. Currently, only a few tools provide the capability of visually organizing networks by cellular compartments. Most of them cannot handle large and dense networks. Even for small networks with hundreds of nodes the available tools are not able to reposition the network while the user is interacting, limiting the visual exploration capability.

resultsHere we propose CellNetVis, a web tool to easily display biological networks in a cell diagram employing a constrained force-directed layout algorithm. The tool is freely available and open-source. It was originally designed for networks generated by the Integrated Interactome System and can be used with networks from others databases, like InnateDB.

conclusionsCellNetVis has demonstrated to be applicable for dynamic investigation of complex networks over a consistent representation of a cell on the Web, with capabilities not matched elsewhere.

Indexed as

InternetMetabolic Networks and PathwaysSoftwareAlgorithmsCellsDatabases, FactualGene OntologyHumansMAP Kinase Signaling SystemUser-Computer InterfaceCell diagramCellNetVisCellular componentForce-directed layoutIISNetwork

Identifiers

PMID28929969
PMCPMC5606216

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.