Evidence map›Paper›PMID 20075183›Full record

ReviewClinical chemistry2010

Protein microarrays for personalized medicine.

Xiaobo Yu, Nicole Schneiderhan-Marra, Thomas O Joos

Abstract readReview
In one paragraph

Review in Clinical chemistry, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.

0numbers the graph read from it
0cells of the map it votes in
39citing 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

39 citing papers in PubMed.

  1. Article
  2. Multi-omics to study chronic respiratory diseases and viral infections.European respiratory review : an official journal of the European Respiratory Society · 2026
    Review
  3. Review
  4. Article
  5. Proteomics appending a complementary dimension to precision oncotherapy.Computational and structural biotechnology journal · 2024
    Review
  6. Review
  7. Review
  8. Review
  9. Review
  10. Review
  11. Review
  12. Review
  13. COVID-19 diagnostic testing: Technology perspective.Clinical and translational medicine · 2020
    Article
  14. Omics for the future in asthma.Seminars in immunopathology · 2020
    Review
  15. Article
  16. Article
  17. Article
  18. Review
  19. Review
  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

3 authors.

Xiaobo YuNMI Natural and Medical Sciences Institute at the University of Tuebingen, Markwiesenstr. 55, 72770 Reutlingen, Germany.
Nicole Schneiderhan-Marra
Thomas O Joos

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOver the last 10 years, DNA microarrays have achieved a robust analytical performance, enabling their use for analyzing the whole transcriptome or for screening thousands of single-nucleotide polymorphisms in a single experiment. DNA microarrays allow scientists to correlate gene expression signatures with disease progression, to screen for disease-specific mutations, and to treat patients according to their individual genetic profiles; however, the real key is proteins and their manifold functions. It is necessary to achieve a greater understanding of not only protein function and abundance but also their role in the development of diseases. Protein concentrations have been shown to reflect the physiological and pathologic state of an organ, tissue, or cells far more directly than DNA, and proteins can be profiled effectively with protein microarrays, which require only a small amount of sample material. CONTENT: Protein microarrays have become well-established tools in basic and applied research, and the first products have already entered the in vitro diagnostics market. This review focuses on protein microarray applications for biomarker discovery and validation, disease diagnosis, and use within the area of personalized medicine. SUMMARY: Protein microarrays have proved to be reliable research tools in screening for a multitude of parameters with only a minimal quantity of sample and have enormous potential in applications for diagnostic and personalized medicine.

Indexed as

BiomarkersDiagnosisHumansPrecision MedicineProtein Array AnalysisBiomarkers

Identifiers

PMID20075183
PMCPMC7108201

What OpenQuestion holds

Textmetadata
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.