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

Emin Arakelian and Fadi Kfoury

EECS Department
University of California, Berkeley
Technical Report No. UCB/EECS-2016-126
July 6, 2016

http://www2.eecs.berkeley.edu/Pubs/TechRpts/2016/EECS-2016-126.pdf

Advisor: Bin Yu


BibTeX citation:

@mastersthesis{Arakelian:EECS-2016-126,
    Author = {Arakelian, Emin and Kfoury, Fadi},
    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-2016-126.html},
    Number = {UCB/EECS-2016-126}
}

EndNote citation:

%0 Thesis
%A Arakelian, Emin
%A Kfoury, Fadi
%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-2016-126
%U http://www2.eecs.berkeley.edu/Pubs/TechRpts/2016/EECS-2016-126.html
%F Arakelian:EECS-2016-126