Evidence map›Paper›PMID 22096234›Full record

ArticleNucleic acids research2012

dbDEPC 2.0: updated database of differentially expressed proteins in human cancers.

Ying He, Menghuan Zhang, Yuanhu Ju, Zhonghao Yu, Daqing Lv, Han Sun, Weilan Yuan, Fei He, Jianshe Zhang, Hong Li and 5 more

Abstract read
In one paragraph

Article in Nucleic acids research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Article
  2. dbGENVOC: database of GENomic Variants of Oral Cancer, with special reference to India.Database : the journal of biological databases and curation · 2021
    Article
  3. Article
  4. Review
  5. DEXTER: Disease-Expression Relation Extraction from Text.Database : the journal of biological databases and curation · 2018
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Human cancer databases (review).Oncology reports · 2015
    Review
  13. Review
  14. Integration of proteomics into systems biology of cancer.Wiley interdisciplinary reviews. Systems biology and medicine
    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

15 authors.

Ying HeKey Laboratory of Systems Biology, Chinese Academy of Sciences, Shanghai 200031, PR of China.
Menghuan Zhang
Yuanhu Ju
Zhonghao Yu
Daqing Lv
Han Sun
Weilan Yuan
Fei He
Jianshe Zhang
Hong Li
Jing Li
Rui Wang-Sattler
Yixue Li
Guoqing Zhang
Lu Xie

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A large amount of differentially expressed proteins (DEPs) have been identified in various cancer proteomics experiments, curation and annotation of these proteins are important in deciphering their roles in oncogenesis and tumor progression, and may further help to discover potential protein biomarkers for clinical applications. In 2009, we published the first database of DEPs in human cancers (dbDEPCs). In this updated version of 2011, dbDEPC 2.0 has more than doubly expanded to over 4000 protein entries, curated from 331 experiments across 20 types of human cancers. This resource allows researchers to search whether their interested proteins have been reported changing in certain cancers, to compare their own proteomic discovery with previous studies, to picture selected protein expression heatmap across multiple cancers and to relate protein expression changes with aberrance in other genetic level. New important developments include addition of experiment design information, advanced filter tools for customer-specified analysis and a network analysis tool. We expect dbDEPC 2.0 to be a much more powerful tool than it was in its first release and can serve as reference to both proteomics and cancer researchers. dbDEPC 2.0 is available at http://lifecenter.sgst.cn/dbdepc/index.do.

Indexed as

Databases, ProteinHumansNeoplasm ProteinsNeoplasmsProteomicsSoftwareNeoplasm Proteins

Identifiers

PMID22096234
PMCPMC3245147

What OpenQuestion holds

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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.