Making sense out of massive data by going beyond differential expression
With the rapid growth of publicly available high-throughput transcriptomic data, there is increasing recognition that large sets of such data can be mined to better understand disease states and mechanisms. Prior gene expression analyses, both large and small, have been dichotomous in nature, in whi...
| Main Authors: | , , , |
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| Other Authors: | , |
| Format: | Article |
| Language: | English |
| Published: |
National Academy of Sciences,
2012-11-15T21:05:43Z.
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| Subjects: | |
| Online Access: | Get fulltext |