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
Advisors: 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