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A hidden Markov support vector machine framework incorporating profile geometry learning for identifying microbial RNA in tiling array data
Motivation: RNA expression signals detected by high-density genomic tiling microarrays contain comprehensive transcriptomic information of the target organism. Current methods for determining the RNA transcription units are still computation intense and lack the discriminative power. This article de...
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| Main Authors: | , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Oxford University Press
2010
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| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC2913668/ https://ncbi.nlm.nih.gov/pubmed/20395286 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/bioinformatics/btq162 |
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