Evidence map›Paper›PMID 23418540›Full record

ArticlePloS one2013

canEvolve: a web portal for integrative oncogenomics.

Mehmet Kemal Samur, Zhenyu Yan, Xujun Wang, Qingyi Cao, Nikhil C Munshi, Cheng Li, Parantu K Shah

Abstract read
In one paragraph

Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing 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

26 citing papers in PubMed.

  1. Article
  2. Article
  3. Prostate cancer in omics era.Cancer cell international · 2022
    Article
  4. Article
  5. Article
  6. MicroRNA Targeting.Methods in molecular biology (Clifton, N.J.) · 2022
    Review
  7. Review
  8. Article
  9. Updates on "Cancer Genomics and Epigenomics".World journal of clinical oncology · 2020
    Review
  10. Systems Biology and Experimental Model Systems of Cancer.Journal of personalized medicine · 2020
    Review
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Review
  17. Article
  18. Article
  19. Article
  20. Review
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.

Mehmet Kemal SamurDepartment of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard School of Public Health, Boston, Massachusetts, United States of America.
Zhenyu Yan
Xujun Wang
Qingyi Cao
Nikhil C Munshi
Cheng Li
Parantu K Shah

Funding

Trageting the Multiple Myeloma EpigenomeP50CA100707 · NCI · DANA-FARBER CANCER INSTITUTE · PI ANDERSON, KENNETH C., MUNSHI, NIKHIL C. · 2003 to 2023
$45.0M
Targeting Genomic Instability and Evolution in MyelomaP01CA155258 · NCI · DANA-FARBER CANCER INST · PI Jill Corre · 2011 to 2026
$32.5M
Targeting Myeloma Cell-Host Bone Marrow InteractionsP01CA078378 · NCI · DANA-FARBER CANCER INSTITUTE · PI RITZ, JEROME · 1998 to 2014
$26.2M
dChip:Analysis and Visualization of Oligonucleotide Expression and SNP ArraysR01GM077122 · NIGMS · DANA-FARBER CANCER INST · PI LI, CHENG · 2008 to 2010
$1.1M
NCI NIH HHS P01 CA078378NCI NIH HHS P01 CA155258NCI NIH HHS P50 CA100707NIGMS NIH HHS R01 GM077122PHS HHS P01-155258PHS HHS P01-78378PHS HHS P50-100007PHS HHS R01-124929
6 · The paper itself

Abstract

BACKGROUND &

objectiveGenome-wide profiles of tumors obtained using functional genomics platforms are being deposited to the public repositories at an astronomical scale, as a result of focused efforts by individual laboratories and large projects such as the Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium. Consequently, there is an urgent need for reliable tools that integrate and interpret these data in light of current knowledge and disseminate results to biomedical researchers in a user-friendly manner. We have built the canEvolve web portal to meet this need.

resultscanEvolve query functionalities are designed to fulfill most frequent analysis needs of cancer researchers with a view to generate novel hypotheses. canEvolve stores gene, microRNA (miRNA) and protein expression profiles, copy number alterations for multiple cancer types, and protein-protein interaction information. canEvolve allows querying of results of primary analysis, integrative analysis and network analysis of oncogenomics data. The querying for primary analysis includes differential gene and miRNA expression as well as changes in gene copy number measured with SNP microarrays. canEvolve provides results of integrative analysis of gene expression profiles with copy number alterations and with miRNA profiles as well as generalized integrative analysis using gene set enrichment analysis. The network analysis capability includes storage and visualization of gene co-expression, inferred gene regulatory networks and protein-protein interaction information. Finally, canEvolve provides correlations between gene expression and clinical outcomes in terms of univariate survival analysis.

conclusionAt present canEvolve provides different types of information extracted from 90 cancer genomics studies comprising of more than 10,000 patients. The presence of multiple data types, novel integrative analysis for identifying regulators of oncogenesis, network analysis and ability to query gene lists/pathways are distinctive features of canEvolve. canEvolve will facilitate integrative and meta-analysis of oncogenomics datasets. AVAILABILITY: The canEvolve web portal is available at http://www.canevolve.org/.

Indexed as

InternetSoftwareDatabases, Nucleic AcidDNA Copy Number VariationsGene Expression ProfilingGene Regulatory NetworksGenomicsHumansInformation Storage and RetrievalMicroRNAsNeoplasmsOncogenesPolymorphism, Single NucleotideReproducibility of ResultsUser-Computer InterfaceMicroRNAs

Identifiers

PMID23418540
PMCPMC3572035

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.