ZipHiC: a novel Bayesian framework to identify enriched interactions and experimental biases in Hi-C data.

Osuntoki, Itunu G; Harrison, Andrew; Dai, Hongsheng; Bao, Yanchun; Zabet, Nicolae Radu

Osuntoki, Itunu G; Harrison, Andrew; Dai, Hongsheng; Bao, Yanchun; Zabet, Nicolae Radu.

Afiliación

Osuntoki IG; Department of Mathematical Sciences, University of Essex, Colchester CO4 3SQ, UK.
Harrison A; Statistics, Modelling and Economics Department, UK Health Security Agency, London NW9 5EQ, UK.
Dai H; Department of Mathematical Sciences, University of Essex, Colchester CO4 3SQ, UK.
Bao Y; Department of Mathematical Sciences, University of Essex, Colchester CO4 3SQ, UK.
Zabet NR; Department of Mathematical Sciences, University of Essex, Colchester CO4 3SQ, UK.

Bioinformatics ; 38(14): 3523-3531, 2022 07 11.

Article en En | MEDLINE | ID: mdl-35678507

Asunto(s)

Drosophila melanogaster; Programas Informáticos; Animales; Teorema de Bayes; Sesgo; ADN; Cromatina

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Texto completo: 1 Base de datos: MEDLINE Asunto principal: Programas Informáticos / Drosophila melanogaster Tipo de estudio: Prognostic_studies Límite: Animals Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2022 Tipo del documento: Article País de afiliación: Reino Unido

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