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Profiling gene expression using onto-express
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AI
DOI：10.1006/geno.2002.6698.png)
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摘要
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Gene expression profiles obtained through microarray or data mining analyses often exist as vast data strings. To interpret the biology of these genetic profiles, investigators must analyze this data in the context of other information such as the biological, biochemical, or molecular function of the translated proteins. This is particularly challenging for a human analyst because large quantities of less than relevant data often bury such information. To address this need we implemented an automated routine, called Onto-Express (http://vortex.cs.wayne.edu:8080), to systematically translate genetic fingerprints into functional profiles. Using strings of accession or cluster identification numbers, Onto-Express searches the public databases and returns tables that correlate expression profiles with the cytogenetic locations, biochemical and molecular functions, biological processes, cellular components, and cellular roles of the translated proteins. The profiles created by Onto-Express fundamentally increase the value of gene expression analyses by facilitating the translation of quantitative value sets to records that contain biological implications.
Keyword:
HUMAN SPERMATOZOA
DNA MICROARRAY
MESSENGER-RNA
PATTERNS
HYBRIDIZATION
TRANSCRIPTS
BIOLOGY
CLUSTER
GENOME
CANCER
期刊
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3
论文数:
7.1K
被引数:
1.2W
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