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Full-Text Articles in Applied Statistics
A Statistical Model To Determine Multiple Binding Sites Of A Transcription Factor On Dna Using Chip-Seq Data, Rasika Jayatillake
A Statistical Model To Determine Multiple Binding Sites Of A Transcription Factor On Dna Using Chip-Seq Data, Rasika Jayatillake
Mathematics & Statistics Theses & Dissertations
Protein-DNA interaction is vital to many biological processes in cells such as cell division, embryo development and regulating gene expression. Chromatin Immunoprecipitation followed by massively parallel sequencing (ChIP-seq) is a new technology that can reveal protein binding sites in genome with superior accuracy. Although many methods have been proposed to find binding sites for ChIP-seq data, they can find only one binding site within a short region of the genome. In this study we introduce a statistical model to identify multiple binding sites of a transcription factor within a short region of the genome using the ChIP-seq data. Mapped sequence …
Analysis Of Discrete Choice Probit Models With Structured Correlation Matrices, Bhaskara Ravi
Analysis Of Discrete Choice Probit Models With Structured Correlation Matrices, Bhaskara Ravi
Mathematics & Statistics Theses & Dissertations
Discrete choice models are very popular in Economics and the conditional logit model is the most widely used model to analyze consumer choice behavior, which was introduced in a seminal paper by McFadden (1974). This model is based on the assumption that the unobserved factors, which determine the consumer choices, are independent and follow a Gumbel distribution, widely known as the Independence of irrelevant Alternatives (IIA) assumption. Alternate models that relax IIA assumption are the Generalized Extreme Value (GEV) models, which allow dependency between unobserved factors. However, GEV models do not incorporate all dependency patterns, other choice behaviors such as …