Improving gene regulatory network inference by incorporating rates of transcriptional change
Organisms respond to changes in their environment through transcriptional regulatory networks (TRNs). The regulatory hierarchy of these networks can be inferred from expression data. Computational approaches to identify TRNs can be applied in any species where quality RNA can be acquired, However, C...
| Autores principales: | , , , , |
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| Formato: | Preprint |
| Lenguaje: | Inglés |
| Publicado: |
Cold Spring Harbor Laboratory
2016
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| Acceso en línea: | https://hdl.handle.net/10568/165166 |
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