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Addressing the unmet need for visualizing conditional random fields in biological data
BACKGROUND: The biological world is replete with phenomena that appear to be ideally modeled and analyzed by one archetypal statistical framework - the Graphical Probabilistic Model (GPM). The structure of GPMs is a uniquely good match for biological problems that range from aligning sequences to mo...
Autores principales: | Ray, William C, Wolock, Samuel L, Callahan, Nicholas W, Dong, Min, Li, Q Quinn, Liang, Chun, Magliery, Thomas J, Bartlett, Christopher W |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4227292/ https://www.ncbi.nlm.nih.gov/pubmed/25000815 http://dx.doi.org/10.1186/1471-2105-15-202 |
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