Evidence map›Paper›PMID 22070249›Full record

ArticleBMC bioinformatics2011

clusterMaker: a multi-algorithm clustering plugin for Cytoscape.

John H Morris, Leonard Apeltsin, Aaron M Newman, Jan Baumbach, Tobias Wittkop, Gang Su, Gary D Bader, Thomas E Ferrin

Abstract read
In one paragraph

Article in BMC bioinformatics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 366 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
366citing papers in PubMed, 1 pooled it
–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

366 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  3. Review
  4. Article
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  6. Article
  7. The topology of adolescent mental health.medRxiv : the preprint server for health sciences · 2026
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  18. SARS-CoV-2 membrane protein biogenesis.bioRxiv : the preprint server for biology · 2026
    Article
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  20. Article

306 more citing papers are in PubMed but not listed here.

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

8 authors.

John H MorrisDepartment of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, California, USA. scooter@cgl.ucsf.edu
Leonard Apeltsin
Aaron M Newman
Jan Baumbach
Tobias Wittkop
Gang Su
Gary D Bader
Thomas E Ferrin

Funding

XRAY CRYSTALLOGRAPHIC STRUCTURE ANALYSIS: PROTEIN SORTINGP41RR001081 · NCRR · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI FERRIN, THOMAS E · 1985 to 2011
$17.6M
TR&D 3 - Network Guided Machine LearningP41GM103504 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI IDEKER, TREY · 2012 to 2024
$17.3M
NCRR NIH HHS P41 RR001081NIGMS NIH HHS P41 GM103504
6 · The paper itself

Abstract

backgroundIn the post-genomic era, the rapid increase in high-throughput data calls for computational tools capable of integrating data of diverse types and facilitating recognition of biologically meaningful patterns within them. For example, protein-protein interaction data sets have been clustered to identify stable complexes, but scientists lack easily accessible tools to facilitate combined analyses of multiple data sets from different types of experiments. Here we present clusterMaker, a Cytoscape plugin that implements several clustering algorithms and provides network, dendrogram, and heat map views of the results. The Cytoscape network is linked to all of the other views, so that a selection in one is immediately reflected in the others. clusterMaker is the first Cytoscape plugin to implement such a wide variety of clustering algorithms and visualizations, including the only implementations of hierarchical clustering, dendrogram plus heat map visualization (tree view), k-means, k-medoid, SCPS, AutoSOME, and native (Java) MCL.

resultsResults are presented in the form of three scenarios of use: analysis of protein expression data using a recently published mouse interactome and a mouse microarray data set of nearly one hundred diverse cell/tissue types; the identification of protein complexes in the yeast Saccharomyces cerevisiae; and the cluster analysis of the vicinal oxygen chelate (VOC) enzyme superfamily. For scenario one, we explore functionally enriched mouse interactomes specific to particular cellular phenotypes and apply fuzzy clustering. For scenario two, we explore the prefoldin complex in detail using both physical and genetic interaction clusters. For scenario three, we explore the possible annotation of a protein as a methylmalonyl-CoA epimerase within the VOC superfamily. Cytoscape session files for all three scenarios are provided in the Additional Files section.

conclusionsThe Cytoscape plugin clusterMaker provides a number of clustering algorithms and visualizations that can be used independently or in combination for analysis and visualization of biological data sets, and for confirming or generating hypotheses about biological function. Several of these visualizations and algorithms are only available to Cytoscape users through the clusterMaker plugin. clusterMaker is available via the Cytoscape plugin manager.

Indexed as

AlgorithmsSoftwareAnimalsCluster AnalysisGenomicsMiceProtein Interaction MapsRacemases and EpimerasesSaccharomyces cerevisiaemethylmalonyl-coenzyme A racemaseRacemases and Epimerases

Identifiers

PMID22070249
PMCPMC3262844

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.