scholarly journals Using Expression Genetics to Study the Neurobiology of Ethanol and Alcoholism

Author(s):  
Sean P. Farris ◽  
Aaron R. Wolen ◽  
Michael F. Miles
Keyword(s):  
1997 ◽  
Vol 20 (2) ◽  
pp. 179-185 ◽  
Author(s):  
M. S. Hershfield ◽  
F. X. Arredondo-Vega ◽  
I. Santisteban

Vascular ◽  
2009 ◽  
Vol 17 (5) ◽  
pp. 253-263 ◽  
Author(s):  
Ian M. Nordon ◽  
Robert J. Hinchliffe ◽  
Peter J. Holt ◽  
Ian M. Loftus ◽  
Matthew M. Thompson

Atherosclerotic plaques are a feature of abdominal aortic aneurysms (AAAs). Atherosclerosis and AAA appear to share similar risk factors. These observations have led to the conclusion that AAAs are a consequence of advanced atherosclerosis. This review explores current theories regarding the pathogenesis of AAA and their implications for treatment. A systematic literature search was conducted using the search terms abdominal aortic aneurysm, atherosclerosis, pathogenesis, and systemic disease. Articles were categorized according to the association of AAAs with atherosclerosis, arteriomegaly, peripheral aneurysm, systemic expression, genetics, autoimmunity, oxidative stress, and systemic disease. Twenty-nine articles reporting changes in the systemic vasculature associated with AAA and 12 articles examining the shared risk factor hypothesis were identified. There is insufficient evidence to confirm that AAAs are the result of advanced atherosclerosis. The bulk of evidence points to AAA disease being a systemic disease of the vasculature, with a predetermined genetic susceptibility leading to a phenotype governed by environmental factors.


2010 ◽  
Vol 6 ◽  
pp. 1744-8069-6-11 ◽  
Author(s):  
Xiangqi Li ◽  
Peyman Sahbaie ◽  
Ming Zheng ◽  
Jennifer Ritchie ◽  
Gary Peltz ◽  
...  

Author(s):  
Triantafyllos Paparountas ◽  
Maria Nefeli Nikolaidou-Katsaridou ◽  
Gabriella Rustici ◽  
Vasilis Aidinis

Microarray technology enables high-throughput parallel gene expression analysis, and use has grown exponentially thanks to the development of a variety of applications for expression, genetics and epigenetic studies. A wealth of data is now available from public repositories, providing unprecedented opportunities for meta-analysis approaches, which could generate new biological information, unrelated to the original scope of individual studies. This study provides a guideline for identification of biological significance of the statistically-selected differentially-expressed genes derived from gene expression arrays as well as to suggest further analysis pathways. The authors review the prerequisites for data-mining and meta-analysis, summarize the conceptual methods to derive biological information from microarray data and suggest software for each category of data mining or meta-analysis.


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