Evidence map›Paper›PMID 22024468›Full record

ArticleJournal of clinical bioinformatics2011

Role of clinical bioinformatics in the development of network-based Biomarkers.

Xiangdong Wang

Abstract read
In one paragraph

Article in Journal of clinical bioinformatics, 2011. 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.

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  15. Gene polymorphisms and chronic obstructive pulmonary disease.Journal of cellular and molecular medicine · 2014
    Article
  16. Article
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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

1 author.

Xiangdong WangBiomedical Research Center, Department of Respiratory Medicine, Fudan University Zhongshan Hospital, China. xiangdong.wang@telia.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Network biomarker as a new type of biomarkers with protein-protein interactions was initiated and investigated with the integration of knowledge on protein annotations, interaction, and signaling pathway. A number of methodologies and computational programs have been developed to integrate selected proteins into the knowledge-based networks via the combination of genomics, proteomics and bioinformatics. Alterations of network biomarkers can be monitored and evaluated at different stages and time points during the development of diseases, named dynamic network biomarkers. Dynamic network biomarkers should be furthermore correlated with clinical informatics, including patient complaints, history, therapies, clinical symptoms and signs, physician's examinations, biochemical analyses, imaging profiles, pathologies and other measurements.

Identifiers

PMID22024468
PMCPMC3221619

What OpenQuestion holds

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Registered trials

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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.