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A generalized linear model for peak calling in ChIP-Seq data
Jialin Xu
, Yu Zhang
Statistics
Institute for Computational and Data Sciences (ICDS)
Huck Institutes of the Life Sciences
Penn State Cancer Institute
Cancer Institute, Mechanisms of Carcinogenesis
Research output
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Contribution to journal
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Article
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peer-review
5
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Scopus citations
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Dive into the research topics of 'A generalized linear model for peak calling in ChIP-Seq data'. Together they form a unique fingerprint.
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Keyphrases
Sequence Data
100%
Massively Parallel Sequencing
100%
Chromatin Immunoprecipitation (ChIP)
100%
Generalized Linear Model
100%
Peak Calling
100%
Genomic Location
40%
Protein-DNA Interaction
40%
Multiple Peaks
20%
Binding Site
20%
Genome Sequencing
20%
DNA Sequencing
20%
Genetic Structure
20%
Local Region
20%
Maximum Likelihood
20%
Interaction Events
20%
Count Data
20%
Binding Profile
20%
Negative Binomial Distribution
20%
Sequencing Data Analysis
20%
Multiple Binding Sites
20%
Sequence Content
20%
Neuroscience
Immunoprecipitation
100%
Deep Sequencing
100%
Generalized Linear Model
100%
Peak Calling
100%
Binding Site
40%
Protein DNA Interaction
40%
DNA Sequencing
20%
Biochemistry, Genetics and Molecular Biology
Deep Sequencing
100%
Chromatin Immunoprecipitation
100%
Peak Calling
100%
Binding Site
40%
Protein-DNA Interaction
40%
Genomics
40%
DNA Sequence
20%
Genomic Structure
20%
Binomial Distribution
20%
Engineering
Binding Site
100%
Strand
50%
Observed Data
50%
Local Region
50%
Maximum Likelihood
50%
Peak Signal
50%
Binomial Distribution
50%
Computer Science
maximum-likelihood
100%
Binomial Distribution
100%