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Identification of Key Factors Regulating Self-renewal and Differentiation in EML Hematopoietic Precursor Cells by RNA-sequencing Analysis
Published on: November 11, 2014
Extracting novel information from gene expression data
1Department of Chemical Engineering and Material Science, Michigan State University, East Lansing, MI 48824, USA.
Abstract:
Data from high throughput technologies, such as DNA microarrays, necessitated the development of new computational methodologies for analyzing the high dimensional information contained within the gene expression data. Liao's group suggested the use of network component analysis to predict transcription factor activities by integrating gene expression data from Escherichia coli with known connectivity information between their genes and transcription factors. This introduces an approach for obtaining novel information from gene expression data.
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