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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...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Public Library of Science
2014
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4236016/ https://www.ncbi.nlm.nih.gov/pubmed/25405334 http://dx.doi.org/10.1371/journal.pone.0108549 |