Predicting Percent Spliced In (PSI) in Alternative Splicing Using Deep Networks

Fadi Kfoury and Emin Arakelian

EECS Department
University of California, Berkeley
Technical Report No. UCB/EECS-2016-127
July 6, 2016

http://www2.eecs.berkeley.edu/Pubs/TechRpts/2016/EECS-2016-127.pdf

Advisor: Bin Yu


BibTeX citation:

@mastersthesis{Kfoury:EECS-2016-127,
    Author = {Kfoury, Fadi and Arakelian, Emin},
    Title = {Predicting Percent Spliced In (PSI) in Alternative Splicing Using Deep Networks},
    School = {EECS Department, University of California, Berkeley},
    Year = {2016},
    Month = {Jul},
    URL = {http://www2.eecs.berkeley.edu/Pubs/TechRpts/2016/EECS-2016-127.html},
    Number = {UCB/EECS-2016-127}
}

EndNote citation:

%0 Thesis
%A Kfoury, Fadi
%A Arakelian, Emin
%T Predicting Percent Spliced In (PSI) in Alternative Splicing Using Deep Networks
%I EECS Department, University of California, Berkeley
%D 2016
%8 July 6
%@ UCB/EECS-2016-127
%U http://www2.eecs.berkeley.edu/Pubs/TechRpts/2016/EECS-2016-127.html
%F Kfoury:EECS-2016-127