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...

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Detalles Bibliográficos
Autores principales: Ray, William C, Wolock, Samuel L, Callahan, Nicholas W, Dong, Min, Li, Q Quinn, Liang, Chun, Magliery, Thomas J, Bartlett, Christopher W
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Research Article
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

Internet

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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