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Items: 4

1.

Optimizing molecular signatures for prostate cancer recurrence

(Submitter supplied) The derivation of molecular signatures indicative of disease status and predictive of subsequent behavior could facilitate the optimal choice of treatment for prostate cancer patients. In this study, we conducted a computational analysis of gene expression profile data obtained from 79 cases, 39 of which were classified as having disease recurrence, to investigate whether advanced computational algorithms can derive more accurate prognostic signatures for prostate cancer. more...
Organism:
Homo sapiens
Type:
Expression profiling by array
Dataset:
GDS4109
Platform:
GPL96
79 Samples
Download data: CEL
Series
Accession:
GSE25136
ID:
200025136
2.
Full record GDS4109

Recurrent and non-recurrent prostate cancer primary tumors

Analysis of prostate cancer primary tumors of known disease recurrence status. Results provide insight into the molecular mechanisms underlying recurrent and non-recurrent prostate cancer primary tumors.
Organism:
Homo sapiens
Type:
Expression profiling by array, count, 2 disease state sets
Platform:
GPL96
Series:
GSE25136
79 Samples
Download data: CEL
3.

[HG-U133A] Affymetrix Human Genome U133A Array

(Submitter supplied) Affymetrix submissions are typically submitted to GEO using the GEOarchive method described at http://www.ncbi.nlm.nih.gov/projects/geo/info/geo_affy.html June 03, 2009: annotation table updated with netaffx build 28 June 08, 2012: annotation table updated with netaffx build 32 June 24, 2016: annotation table updated with netaffx build 35 Protocol: see manufacturer's web site The U133 set includes 2 arrays with a total of 44928 entries and was indexed 29-Jan-2002. more...
Organism:
Homo sapiens
364 DataSets
1125 Series
11 Related Platforms
42430 Samples
Download data
Platform
Accession:
GPL96
ID:
100000096
4.

Prostate cancer primary tumor PR2

Organism:
Homo sapiens
Source name:
Human prostate cancer
Platform:
GPL96
Series:
GSE25136
Dataset:
GDS4109
Download data: CEL
Sample
Accession:
GSM617604
ID:
300617604
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