Evidence map›Paper›PMID 11298187›Full record

ReviewInternational journal of experimental pathology2000

Subtractive hybridization--genetic takeaways and the search for meaning.

R J Byers, J A Hoyland, J Dixon, A J Freemont

Open access · greenAbstract readReview
In one paragraph

Review in International journal of experimental pathology, 2000. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.7field-weighted citation impact, top 16% of its field
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

6 citing papers in PubMed, 37 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Clusterin as a biomarker in murine and human intestinal neoplasia.Proceedings of the National Academy of Sciences of the United States of America · 2003
    Article
  5. Article
  6. Article
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

4 authors at 1 institution in 1 country.

R J ByersLaboratory Medicine Academic Group, University of Manchester, Manchester, UK. r.byers@man.ac.uk
J A Hoyland
J Dixon
A J Freemont
University of Manchester · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gene expression profiling relies on mRNA extraction from defined cell systems, which in the case of pathological processes necessarily results in the use of small quantities of tissues, sometimes as little as a few cells. This obviates the use of many systems of gene expression profiling and is best carried out using cDNA amplified by poly(A) reverse transcription polymerase chain reaction, which is capable of generating material representative of all the expressed genes in samples as small as one cell. Analysis of this material using subtractive hybridization compares the genes expressed at different stages of a biological/pathological process allowing identification of the all the genes upregulated during the process. The identification of the genes present is not dependent on their prior description or on the choice of genes used in a screen and as such the method is ideal for identifying novel genes or unsuspected genes. We have used the method to identify genes involved in normal osteoblastic differentiation and in Paget's disease of bone and it has been widely used to study normal differentiation and pathological processes in a number of systems. The method, its applications and its relationship with the other methods of gene expression profiling are reviewed.

Indexed as

Cell DifferentiationExpressed Sequence TagsGene Expression ProfilingGene Expression RegulationHumansIn Situ HybridizationNeoplasmsOligonucleotide Array Sequence AnalysisReverse Transcriptase Polymerase Chain Reaction

Identifiers

PMID11298187
PMCPMC2517747
OpenAlexW1903840298

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.