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Prediction of CRISPR-Cas9 Cleavage Efficiency Through Markov Feature Engineering and Boosting-Based Transfer Learning

Description:

In the short amount of time that genetic manipulation has been possible through CRISPR technology, myriad applications have been developed. Results from one of the most promising applications of this technology, pooled screens, have shown that single guide RNAs (sgRNAs), RNA sequences used to target specific regions of the genome,...

Keyword:

sgRNA design, CRISPR efficiency, and Machine learning

Subject:

Biostatistics, Statistics, and Bioinformatics

Creator:

Zarate, Oscar Alberto

Owner:

Scholarly Digital Publishing

Language:

en

Date Uploaded:

02/01/2021

Date Created:

2020-01-01

Resource Type:

Dissertation

Alternate Identifier:

http://dissertations.umi.com/northwestern:15353 and etdadmin_upload_773909