Alpha-2-macroglobulin RNA [primary]
Experiment Id: 2443 Pattern Id: GC11845 Clone number: 108288 GenBank Acc: T70551 |
Rationale: Relative RNA levels for nearly 10,000 human clones were measured in a microarray experiment. Some of these clones have been linked to known genes (based on clustering information from Unigene) - follow the links to Unigene and GeneCards, where information on possible function can be found. Other clones represent as yet unnamed genes - follow the Unigene link for more information. All gene assignments should be considered tentative. Sequence information for a clone can be found through GenBank or Unigene, and can be used to search sequence databases. |
Investigator(s): Botstein, Dr. David Stanford University School of Medicine Weinstein, Dr. John National Cancer Institute |
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Method: Microarray Unit: log(mRNA levels in cell line/mRNA levels in reference pool) Protocol: mRNA was isolated from logarithmically growing cells. Labelled cDNA was prepared by reverse transcription of test cell mRNA in the presence of Cy5-dUTP. Reference probes were made by pooling equal amounts of mRNA from HL-60, K562, NCI-H226, COLO205, SNB-19, LOX-IMVI, OVCAR-3, OVCAR-4, CAKI-1, PC-3, MCF7 and Hs578T cell lines. Labelled cDNA was prepared from the pooled mRNA by reverse transcription in the presence of Cy3-dUTP. Test and reference probes were combined, denatured and hybridized overnight to Synteni microarrays containing cDNA from 9703 human clones. Arrays were scanned using a laser-scanning microscope. The ScanAlyze program was used to analyze the microarray images and prepare data files for further analysis. |
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An experimental system for automatically partitioning GenBank sequences into a non-redundant set of gene-oriented clusters. |
Presents information on official nomenclature, aliases, sequence accession numbers, phenotypes, EC numbers, MIM numbers, UniGene clusters, map information, Gene Ontology annotations, and relevant web sites. Replaces LocusLink. |
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A catalog of human genes and genetic disorders. |
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CGAP provides information on gene expression, SNPs, functional pathways and more in normal, precancerous and cancer cells. |
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