Evidence map›Paper›PMID 17893073›Full record

ReviewGenomics, proteomics & bioinformatics2007

Proteomics technologies and challenges.

William C S Cho

Abstract readReview
In one paragraph

Review in Genomics, proteomics & bioinformatics, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 78 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
78citing papers in PubMed, 3 pooled it
–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

78 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Trial
  5. Article
  6. Article
  7. Review
  8. Review
  9. Review
  10. Review
  11. Proteomic Technology.Advances in experimental medicine and biology · 2026
    Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Review
  18. Review
  19. Review
  20. Proteomic profiling ofTurkish journal of biology = Turk biyoloji dergisi · 2025
    Article

18 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

1 author.

William C S ChoDepartment of Clinical Oncology, Queen Elizabeth Hospital, Hong Kong, China. chocs@ha.org.hk

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Proteomics is the study of proteins and their interactions in a cell. With the completion of the Human Genome Project, the emphasis is shifting to the protein compliment of the human organism. Because proteome reflects more accurately on the dynamic state of a cell, tissue, or organism, much is expected from proteomics to yield better disease markers for diagnosis and therapy monitoring. The advent of proteomics technologies for global detection and quantitation of proteins creates new opportunities and challenges for those seeking to gain greater understanding of diseases. High-throughput proteomics technologies combining with advanced bioinformatics are extensively used to identify molecular signatures of diseases based on protein pathways and signaling cascades. Mass spectrometry plays a vital role in proteomics and has become an indispensable tool for molecular and cellular biology. While the potential is great, many challenges and issues remain to be solved, such as mining low abundant proteins and integration of proteomics with genomics and metabolomics data. Nevertheless, proteomics is the foundation for constructing and extracting useful knowledge to biomedical research. In this review, a snapshot of contemporary issues in proteomics technologies is discussed.

Indexed as

Computational BiologyForecastingHumansMass SpectrometryProtein Array AnalysisProteinsProteomicsProteins

Identifiers

PMID17893073
PMCPMC5054093

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.