A Macintosh program for storage and analysis of experimental genetic mapping data

1993 ◽  
Vol 4 (6) ◽  
pp. 303-313 ◽  
Author(s):  
Kenneth F. Manly

PLoS ONE ◽  
2007 ◽  
Vol 2 (10) ◽  
pp. e1036 ◽  
Author(s):  
Jeremy L. Peirce ◽  
Karl W. Broman ◽  
Lu Lu ◽  
Robert W. Williams


2007 ◽  
Vol 32 (1) ◽  
pp. 45-57 ◽  
Author(s):  
Shantel Weinsheimer ◽  
Guy M. Lenk ◽  
Monique van der Voet ◽  
Susan Land ◽  
Antti Ronkainen ◽  
...  

Intracranial aneurysm (IA) is a complex genetic disease for which, to date, 10 loci have been identified by linkage. Identification of the risk-conferring genes in the loci has proven difficult, since the regions often contain several hundreds of genes. An approach to prioritize positional candidate genes for further studies is to use gene expression data from diseased and nondiseased tissue. Genes that are not expressed, either in diseased or nondiseased tissue, are ranked as unlikely to contribute to the disease. We demonstrate an approach for integrating expression and genetic mapping data to identify likely pathways involved in the pathogenesis of a disease. We used expression profiles for IAs and nonaneurysmal intracranial arteries (IVs) together with the 10 reported linkage intervals for IA. Expressed genes were analyzed for membership in Kyoto Encyclopedia of Genes and Genomes (KEGG) biological pathways. The 10 IA loci harbor 1,858 candidate genes, of which 1,561 (84%) were represented on the microarrays. We identified 810 positional candidate genes for IA that were expressed in IVs or IAs. Pathway information was available for 294 of these genes and involved 32 KEGG biological function pathways represented on at least 2 loci. A likelihood-based score was calculated to rank pathways for involvement in the pathogenesis of IA. Adherens junction, MAPK, and Notch signaling pathways ranked high. Integration of gene expression profiles with genetic mapping data for IA provides an approach to identify candidate genes that are more likely to function in the pathology of IA.



Author(s):  
J. W. Van Ooijen ◽  
J. Jansen


2000 ◽  
Author(s):  
Cheryl Stauffer
Keyword(s):  


2009 ◽  
pp. 27-53
Author(s):  
A. Yu. Kudryavtsev

Diversity of plant communities in the nature reserve “Privolzhskaya Forest-Steppe”, Ostrovtsovsky area, is analyzed on the basis of the large-scale vegetation mapping data from 2000. The plant community classi­fication based on the Russian ecologic-phytocoenotic approach is carried out. 12 plant formations and 21 associations are distinguished according to dominant species and a combination of ecologic-phytocoenotic groups of species. A list of vegetation classification units as well as the characteristics of theshrub and woody communities are given in this paper.



2011 ◽  
Vol 37 (10) ◽  
pp. 1779-1784
Author(s):  
Ming-Jing ZHOU ◽  
Yong WEN ◽  
Shuang-Cheng LI ◽  
Cheng-Bo LI ◽  
Man-Hua ZHANG ◽  
...  


2020 ◽  
Author(s):  
Jessica Harryman ◽  
◽  
Ryan O'Connor ◽  
Adriana Pena ◽  
Christina Viviano ◽  
...  
Keyword(s):  


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