Modeling positional effects of regulatory sequences with spline transformations increases prediction accuracy of deep neural networks-Reference-Cited by-同舟云学术

Modeling positional effects of regulatory sequences with spline transformations increases prediction accuracy of deep neural networks

Published:2017-11-16 Issue:8 Volume:34 Page:1261-1269
ISSN:1367-4803
Container-title:Bioinformatics
language:en
Short-container-title:

Author:

Avsec Žiga¹²,Barekatain Mohammadamin¹^ORCID,Cheng Jun¹²,Gagneur Julien¹

Affiliation:

1. Department of Informatics, Technical University of Munich, Garching, Germany

2. Graduate School of Quantitative Biosciences (QBM), Gene Center, Ludwig-Maximilians-Universität München, Munich, Germany

Funder

Deutsche Forschungsgemeinschaft

Nvidia

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

Link

http://academic.oup.com/bioinformatics/article-pdf/34/8/1261/25171174/btx727.pdf

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2. DeepCpG: accurate prediction of single-cell DNA methylation states using deep learning;Angermueller;Genome Biol,2017

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