Evidence map›Paper›PMID 19465394›Full record

ArticleNucleic acids research2009

VisANT 3.5: multi-scale network visualization, analysis and inference based on the gene ontology.

Zhenjun Hu, Jui-Hung Hung, Yan Wang, Yi-Chien Chang, Chia-Ling Huang, Matt Huyck, Charles DeLisi

Abstract read
In one paragraph

Article in Nucleic acids research, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 86 papers.

0numbers the graph read from it
0cells of the map it votes in
86citing 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

86 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Article
  6. Review
  7. A Guide to Conquer the Biological Network Era Using Graph Theory.Frontiers in bioengineering and biotechnology · 2020
    Review
  8. Article
  9. Article
  10. Review
  11. Article
  12. Methods, Tools and Current Perspectives in Proteogenomics.Molecular & cellular proteomics : MCP · 2017
    Review
  13. Weighted gene co-expression network analysis of gene modules for the prognosis of esophageal cancer.Journal of Huazhong University of Science and Technology. Medical sciences = Hua zhong ke ji da xue xue bao. Yi xue Ying De wen ban = Huazhong keji daxue xuebao. Yixue Yingdewen ban · 2017
    Article
  14. Review
  15. Review
  16. Review
  17. Article
  18. Article
  19. Article
  20. KnowEnG: a knowledge engine for genomics.Journal of the American Medical Informatics Association : JAMIA · 2015
    Article

26 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

7 authors.

Zhenjun HuCenter for Advanced Genomic Technology, Program in Bioinformatics, Boston University, Boston, MA 02215, USA. zhenjun.hu@gmail.com
Jui-Hung Hung
Yan Wang
Yi-Chien Chang
Chia-Ling Huang
Matt Huyck
Charles DeLisi

Funding

Visant-Predictome: A System for Integration, Mining, Visualization and AnalysisR01RR022971 · NCRR · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · PI DELISI, CHARLES, HU, ZHENJUN · 2007 to 2011
$2.1M
New Methods for Cancer Class Discovery and Prediction: Integration, visualizationR21CA135882 · NCI · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · PI DELISI, CHARLES · 2008 to 2009
$447k
NCI NIH HHS 1R21CA135882-01NCRR NIH HHS 1R01RR022971-01A1NCRR NIH HHS R01 RR022971
6 · The paper itself

Abstract

Despite its wide usage in biological databases and applications, the role of the gene ontology (GO) in network analysis is usually limited to functional annotation of genes or gene sets with auxiliary information on correlations ignored. Here, we report on new capabilities of VisANT--an integrative software platform for the visualization, mining, analysis and modeling of the biological networks--which extend the application of GO in network visualization, analysis and inference. The new VisANT functions can be classified into three categories. (i) Visualization: a new tree-based browser allows visualization of GO hierarchies. GO terms can be easily dropped into the network to group genes annotated under the term, thereby integrating the hierarchical ontology with the network. This facilitates multi-scale visualization and analysis. (ii) Flexible annotation schema: in addition to conventional methods for annotating network nodes with the most specific functional descriptions available, VisANT also provides functions to annotate genes at any customized level of abstraction. (iii) Finding over-represented GO terms and expression-enriched GO modules: two new algorithms have been implemented as VisANT plugins. One detects over-represented GO annotations in any given sub-network and the other finds the GO categories that are enriched in a specified phenotype or perturbed dataset. Both algorithms take account of network topology (i.e. correlations between genes based on various sources of evidence). VisANT is freely available at http://visant.bu.edu.

Indexed as

Gene Regulatory NetworksModels, GeneticSoftwareAlgorithmsCell CycleComputer GraphicsHumansInternetSystems Integration

Identifiers

PMID19465394
PMCPMC2703932

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.