Publication Date
Spring 2012
Degree Type
Master's Project
Degree Name
Master of Science (MS)
Department
Computer Science
Abstract
This project uses the characteristic in TATA-less regions on E. coli sequences to predict the promoter region before TSS, which indicate that the real gene has been located. It uses several well-known algorithms and methods such as the sliding window algorithm, and a clustering method to predict promoters. It also contains D2K algorithm and method to compare predicted result with other online promoter package result.
Recommended Citation
Wen, Li, "Promoter Prediction Based on E. coli Characteristics" (2012). Master's Projects. 216.
DOI: https://doi.org/10.31979/etd.tcpk-tx2n
https://scholarworks.sjsu.edu/etd_projects/216
