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Improving GRN re‐construction by mining hidden regulatory signals
Inferring gene regulatory networks (GRNs) from gene expression data is an important but challenging issue in systems biology. Here, the authors propose a dictionary learning‐based approach that aims to infer GRNs by globally mining regulatory signals, known or latent. Gene expression is often regula...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
The Institution of Engineering and Technology
2017
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8687237/ https://www.ncbi.nlm.nih.gov/pubmed/29125126 http://dx.doi.org/10.1049/iet-syb.2017.0013 |