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Stroke Genomics: Approaches to Identify, Validate, and Understand Ischemic Stroke Gene Expression
Journal article   Open access   Peer reviewed

Stroke Genomics: Approaches to Identify, Validate, and Understand Ischemic Stroke Gene Expression

Simon J Read, Andrew A Parsons, David C Harrison, Karen Philpott, Karen Kabnick, Shawn O'Brien, Steven Clark, Mary Brawner, Stewart Bates, Israel Gloger, …
Journal of cerebral blood flow and metabolism, v 21(7), pp 755-778
Jul 2001
PMID: 11435788
url
https://doi.org/10.1097/00004647-200107000-00001View
Published, Version of Record (VoR) Open

Abstract

Sequencing of the human genome is nearing completion and biologists, molecular biologists, and bioinformatics specialists have teamed up to develop global genomic technologies to help decipher the complex nature of pathophysiologic gene function. This review will focus on differential gene expression in ischemic stroke. It will discuss inheritance in the broader stroke population, how experimental models of spontaneous stroke might be applied to humans to identify chromosomal loci of increased risk and ischemic sensitivity, and also how the gene expression induced by stroke is related to the poststroke processes of brain injury, repair, and recovery. In addition, we discuss and summarise the literature of experimental stroke genomics and compare several approaches of differential gene expression analyzes. These include a comparison of representational difference analysis we have provided using an experimental stroke model that is representative of stroke evolution observed most often in man, and a summary of available data on stroke differential gene expression. Issues regarding validation of potential genes as stroke targets, the verification of message translation to protein products, the relevance of the expression of neuroprotective and neurodestructive genes and their specific timings, and the emerging problems of handling novel genes that may be discovered during differential gene expression analyses will also be addressed.

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Collaboration types
International collaboration
Web of Science research areas
Endocrinology & Metabolism
Hematology
Neurosciences
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