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- W2589163046 abstract "Chromatin ImmunoPrecipitation-sequencing (ChIP-seq) experiments have now become routine in biology for the detection of protein binding sites. In this chapter, we show how hidden Markov models can be used for the analysis of data generated by ChIP-seq experiments. We show how a hidden Markov model can naturally account for spatial dependencies in the ChIP-seq data, how it can be used in the presence of data from multiple ChIP-seq experiments under the same biological condition, and how it naturally accounts for the different IP efficiencies of individual ChIP-seq experiments." @default.
- W2589163046 created "2017-03-03" @default.
- W2589163046 creator A5048072558 @default.
- W2589163046 date "2017-01-01" @default.
- W2589163046 modified "2023-09-26" @default.
- W2589163046 title "Modelling ChIP-seq Data Using HMMs" @default.
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- W2589163046 doi "https://doi.org/10.1007/978-1-4939-6753-7_8" @default.
- W2589163046 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/28224494" @default.
- W2589163046 hasPublicationYear "2017" @default.
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