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Life Sciences Commons

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Genetics and Genomics

Dartmouth College

1999

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Full-Text Articles in Life Sciences

Cbfa2 Is Required For The Formation Of Intra-Aortic Hematopoietic Clusters, Trista North, Ting-Lei Gu, Stacy Terryl, Qing Wang, Louisa Howard, Michael Binder, Miguel Marín-Padilla, Nancy A. Speck May 1999

Cbfa2 Is Required For The Formation Of Intra-Aortic Hematopoietic Clusters, Trista North, Ting-Lei Gu, Stacy Terryl, Qing Wang, Louisa Howard, Michael Binder, Miguel Marín-Padilla, Nancy A. Speck

Dartmouth Scholarship

Cbfa2 (AML1) encodes the DNA-binding subunit of a transcription factor in the small family of core-binding factors (CBFs). Cbfa2 is required for the differentiation of all definitive hematopoietic cells, but not for primitive erythropoiesis. Here we show that Cbfa2 is expressed in definitive hematopoietic progenitor cells, and in endothelial cells in sites from which these hematopoietic cells are thought to emerge. Endothelial cells expressing Cbfa2 are in the yolk sac, the vitelline and umbilical arteries, and in the ventral aspect of the dorsal aorta in the aorta/genital ridge/mesonephros (AGM) region. Endothelial cells lining the dorsal aspect of the aorta, and …


Interpreting Patterns Of Gene Expression With Self-Organizing Maps: Methods And Application To Hematopoietic Differentiation, Pablo Tamayo, Donna Slonim, Jill Mesirov, Qing Zhu, Sutisak Kitareewan, Ethan Dmitrovsky Mar 1999

Interpreting Patterns Of Gene Expression With Self-Organizing Maps: Methods And Application To Hematopoietic Differentiation, Pablo Tamayo, Donna Slonim, Jill Mesirov, Qing Zhu, Sutisak Kitareewan, Ethan Dmitrovsky

Dartmouth Scholarship

Array technologies have made it straightforward to monitor simultaneously the expression pattern of thousands of genes. The challenge now is to interpret such massive data sets. The first step is to extract the fundamental patterns of gene expression inherent in the data. This paper describes the application of self-organizing maps, a type of mathematical cluster analysis that is particularly well suited for recognizing and classifying features in complex, multidimensional data. The method has been implemented in a publicly available computer package, GENECLUSTER, that performs the analytical calculations and provides easy data visualization. To illustrate the value of such analysis, the …