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
Advisors: 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