dc.contributor.advisor | Gillevet, Patrick M | |
dc.contributor.author | Dadkhah, Ezzat![]() |
|
dc.creator | Dadkhah, Ezzat | |
dc.date.accessioned | 2018-10-22T01:19:56Z | |
dc.date.available | 2018-10-22T01:19:56Z | |
dc.date.issued | 2017 | |
dc.identifier.uri | https://hdl.handle.net/1920/11285 | |
dc.description.abstract | Colorectal cancer (CRC) results from a complex interplay between genes and the environment. Recent studies have focused on the gut microbial population (the microbiota) and its aggregate genome (the microbiome) as one of the environmental players in colorectal tumorigenesis. High-throughput sequencing techniques have added a new dimension to the mining of gut microbiome for biomarkers of CRC and therapeutic targets. Current approaches to microbiome analysis include quantifying the relative abundancies and diversities of microbial populations along with the identification of disease-specific biomarkers. | |
dc.format.extent | 244 pages | |
dc.language.iso | en | |
dc.rights | Copyright 2017 Ezzat Dadkhah | |
dc.subject | Biology | en_US |
dc.subject | Bioinformatics | en_US |
dc.subject | Classification | en_US |
dc.subject | Colorectal cancer | en_US |
dc.subject | Machine learning | en_US |
dc.subject | Microbiome | en_US |
dc.subject | OTU | en_US |
dc.subject | Statistical tests | en_US |
dc.title | Microbiome Analysis in Colorectal Cancer | |
dc.type | Dissertation | |
thesis.degree.level | Ph.D. | |
thesis.degree.discipline | Biosciences | |
thesis.degree.grantor | George Mason University |