Open Access. Powered by Scholars. Published by Universities.®
- Keyword
Articles 1 - 3 of 3
Full-Text Articles in Entire DC Network
Zero-Inflated Models To Identify Transcription Factor Binding Sites In Chip-Seq Experiments, Sameera Dhananjaya Viswakula
Zero-Inflated Models To Identify Transcription Factor Binding Sites In Chip-Seq Experiments, Sameera Dhananjaya Viswakula
Mathematics & Statistics Theses & Dissertations
It is essential to determine the protein-DNA binding sites to understand many biological processes. A transcription factor is a particular type of protein that binds to DNA and controls gene regulation in living organisms. Chromatin immunoprecipitation followed by highthroughput sequencing (ChIP-seq) is considered the gold standard in locating these binding sites and programs use to identify DNA-transcription factor binding sites are known as peak-callers. ChIP-seq data are known to exhibit considerable background noise and other biases. In this study, we propose a negative binomial model (NB), a zero-inflated Poisson model (ZIP) and a zero-inflated negative binomial model (ZINB) for peak-calling. …
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 …
Improved Constrained Global Optimization For Estimating Molecular Structure From Atomic Distances, Terri Marie Grant
Improved Constrained Global Optimization For Estimating Molecular Structure From Atomic Distances, Terri Marie Grant
Mathematics & Statistics Theses & Dissertations
Determination of molecular structure is commonly posed as a nonlinear optimization problem. The objective functions rely on a vast amount of structural data. As a result, the objective functions are most often nonconvex, nonsmooth, and possess many local minima. Furthermore, introduction of additional structural data into the objective function creates barriers in finding the global minimum, causes additional computational issues associated with evaluating the function, and makes physical constraint enforcement intractable. To combat the computational problems associated with standard nonlinear optimization formulations, Williams et al. (2001) proposed an atom-based optimization, referred to as GNOMAD, which complements a simple interatomic distance …