Evidence map›Paper›PMID 18764911›Full record

ReviewPediatric transplantation2008

The proteogenomic path towards biomarker discovery.

Tara K Sigdel, Minnie M Sarwal

Abstract readReview
In one paragraph

Review in Pediatric transplantation, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 1 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

27 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Bioinformatics for Renal and Urinary Proteomics: Call for Aggrandization.International journal of molecular sciences · 2020
    Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Molecular monitoring of alloimmune-mediated injury in kidney transplant patients.Current opinion in nephrology and hypertension · 2014
    Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. Review
  19. Applications of translational bioinformatics in transplantation.Clinical pharmacology and therapeutics · 2011
    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

2 authors.

Tara K SigdelDepartment of Pediatrics-Nephrology, Stanford University Medical School, Stanford University, Stanford, CA 94305, USA.
Minnie M Sarwal

Funding

Defining Biomarkers in Pediatric Renal TransplantationR01AI061739 · NIAID · STANFORD UNIVERSITY · PI SARWAL, MINNIE M · 2004 to 2007
$1.6M
NIAID NIH HHS R01 AI061739
6 · The paper itself

Abstract

The desire for biomarkers for diagnosis and prognosis of diseases has never been greater. With the availability of genome data and an increased availability of proteome data, the discovery of biomarkers has become increasingly feasible. However, the task is daunting and requires collaborations among researchers working in the fields of transplantation, immunology, genetics, molecular biology, biostatistics and bioinformatics. With the advancement of high throughput omic techniques such as genomics and proteomics (collectively known as proteogenomics), efforts have been made to develop diagnostic tools from new and to-be discovered biomarkers. Yet biomarker validation, particularly in organ transplantation, remains challenging because of the lack of a true gold standard for diagnostic categories and analytical bottlenecks that face high-throughput data deconvolution. Even though microarray technique is relatively mature, proteomics is still growing with regards to data normalization and analysis methods. Study design, sample selection and rigorous data analysis are the critical issues for biomarker discovery using high-throughput proteogenomic technologies that combine the use and strengths of both genomics and proteomics. In this review, we look into the current status and latest developments in the field of biomarker discovery using genomics and proteomics related to organ transplantation, with an emphasis on the evolution of proteomic technologies.

Indexed as

AnimalsBiomarkersComputational BiologyGenomeGenomicsGraft RejectionHumansImmunosuppressive AgentsKidney TransplantationMiceOligonucleotide Array Sequence AnalysisOrgan TransplantationPeptidesProteomicsRatsBiomarkersImmunosuppressive AgentsPeptides

Identifiers

PMID18764911
PMCPMC2574627

What OpenQuestion holds

Textmetadata
LicenceTDM
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.