Graduate Thesis Or Dissertation
 

Prediction of gene transcription start sites and initiation patterns from DNA sequence content

Público Deposited

Contenido Descargable

Descargar PDF
https://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/1c18dj14q

Descriptions

Attribute NameValues
Creator
Abstract
  • The computational identification of gene Transcription Start Sites (TSSs) can provide insights into the regulation and function of genes without performing expensive experiments, particularly in organisms with incomplete annotations. High-resolution general-purpose TSS prediction remains a challenging problem, with little recent progress on the identification and differentiation of TSSs which are arranged in different spatial patterns along the chromosome. In this work, we present TIPR, a sequence-based machine learning model which identifies TSSs with high accuracy and resolution for multiple spatial distribution patterns along the genome, including broadly distributed TSS patterns which have previously been difficult to characterize. TIPR predicts not only the locations of TSSs, but also the expected spatial initiation pattern each TSS will form along the chromosome--a novel capability for TSS prediction algorithms. As spatial initiation patterns are associated with spatiotemporal expression patterns and gene function, this capability has the potential to improve gene annotations and our understanding of the regulation of transcription initiation. The high nucleotide-resolution of this model locates TSSs within 10 nucleotides or less on average.
License
Resource Type
Fecha Disponible
Fecha de Emisión
Degree Level
Degree Name
Degree Field
Degree Grantor
Commencement Year
Advisor
Committee Member
Academic Affiliation
Non-Academic Affiliation
Subject
Declaración de derechos
Publisher
Peer Reviewed
Language
Replaces

Relaciones

Parents:

This work has no parents.

En Collection:

Elementos

Miniatura Título Fecha de subida Visibilidad Acciones
file details MortonTajH2014_Corrected.pdf 2017-08-07 Público Descargar