Evidence map›Paper›PMID 10613842›Full record

ArticleGenome research1999

Prediction of gene function by genome-scale expression analysis: prostate cancer-associated genes.

M G Walker, W Volkmuth, E Sprinzak, D Hodgson, T Klingler

Open access · bronzeAbstract read
In one paragraph

Article in Genome research, 1999. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 63 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
63citing 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

63 citing papers in PubMed, 1 synthesis or guideline pooled it, 172 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Artificial Intelligence for Plant Gene Regulatory Networks.International journal of molecular sciences · 2026
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  4. Triclustering Model for Three-Dimensional Time-Series Gene Expression Data.International journal of molecular sciences · 2026
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  6. Sustainable integrative cell biology: CENP-C is guilty by association.Chromosome research : an international journal on the molecular, supramolecular and evolutionary aspects of chromosome biology · 2025
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  10. Article
  11. Article
  12. Article
  13. Article
  14. HpeNet: Co-expression Network Database forFrontiers in genetics · 2020
    Article
  15. Article
  16. Article
  17. Article
  18. Exploration of gene functions for esophageal squamous cell carcinoma using network-based guilt by association principle.Brazilian journal of medical and biological research = Revista brasileira de pesquisas medicas e biologica · 2018
    Article
  19. Article
  20. Article

3 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

5 authors at 1 institution in 1 country.

M G WalkerIncyte Pharmaceuticals, Palo Alto, California 94304, USA. mwalker@incyte.com
W Volkmuth
E Sprinzak
D Hodgson
T Klingler
Incyte (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We wish to identify genes associated with disease. To do so, we look for novel genes whose expression patterns mimic those of known disease-associated genes, using a method we call Guilt-by-Association (GBA), on the basis of a combinatoric measure of association. Using GBA, we have examined the expression of 40,000 human genes in 522 cDNA libraries, and have discovered several hundred previously unidentified genes associated with cancer, inflammation, steroid-synthesis, insulin-synthesis, neurotransmitter processing, matrix remodeling, and other disease processes. The majority of the genes thus discovered show no sequence similarity to known genes, and thus could not have been identified by homology searches. We present here an example of the discovery of eight genes associated with prostate cancer. Of the 40,000 most-abundant human genes, these 8 are the most closely linked to the known diagnostic genes, and thus are prime targets for pharmaceutical research.

Indexed as

Gene Expression ProfilingGene Expression Regulation, NeoplasticHumansMaleMolecular Sequence DataProstatic NeoplasmsProto-Oncogene ProteinsProto-Oncogene Proteins

Identifiers

PMID10613842
PMCPMC310991
OpenAlexW2152689720

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.