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Computational Surprisal Analysis Speeds-Up Genomic Characterization of Cancer Processes
Surprisal analysis is increasingly being applied for the examination of transcription levels in cellular processes, towards revealing inner network structures and predicting response. But to achieve its full potential, surprisal analysis should be integrated into a wider range computational tool. Th...
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| Publicado no: | PLoS One |
|---|---|
| Main Authors: | , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Public Library of Science
2014
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4236016/ https://ncbi.nlm.nih.gov/pubmed/25405334 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0108549 |
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