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This paper applies a deep convolutional/highway MLP framework to classify genomic sequences on the transcription factor binding site task.
Dna binding sites: representation and discovery
Gary D Stormo · 2000
Earlier work this paper cites.
Quantifying similarity between motifs
Shobhit Gupta, John A Stamatoyannopoulos, Timothy L Bailey, and William S Noble · 2007
Earlier work this paper cites.
Meme suite: tools for motif discovery and searching
Timothy L Bailey, Mikael Boden, Fabian A Buske, Martin Frith, Charles E Grant, Luca Clementi, Jingyuan Ren, Wilfred W Li, and William S Noble · 2009
Earlier work this paper cites.
Assigning roles to dna regulatory motifs using comparative genomics
Fabian A Buske, Mikael Bodén, Denis C Bauer, and Timothy L Bailey · 2010
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An integrated encyclopedia of dna elements in the human genome
ENCODE Project Consortium et al · 2012
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Deep inside convolutional networks: Visualising image classification models and saliency maps
Karen Simonyan, Andrea Vedaldi, and Andrew Zisserman · 2013
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Modeling the specificity of protein-dna interactions
Gary D Stormo · 2013
Earlier work this paper cites.
Enhanced regulatory sequence prediction using gapped k-mer features
Mahmoud Ghandi, Dongwon Lee, Morteza Mohammad-Noori, and Michael A Beer · 2014
Cited alongside, same era.
Decoding chip-seq with a double-binding signal refines binding peaks to single-nucleotides and predicts cooperative interaction
Antonio LC Gomes, Thomas Abeel, Matthew Peterson, Elham Azizi, Anna Lyubetskaya, Luís Carvalho, and James Galagan · 2014
Cited alongside, same era.
Dropout: A simple way to prevent neural networks from overfitting
Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov · 2014
Cited alongside, same era.
Predicting the sequence specificities of dna-and rna-binding proteins by deep learning
Babak Alipanahi, Andrew Delong, Matthew T Weirauch, and Brendan J Frey · 2015
Cited alongside, same era.
Character-aware neural language models
Yoon Kim, Yacine Jernite, David Sontag, and Alexander M Rush · 2015
Cited alongside, same era.
Training very deep networks
Rupesh K Srivastava, Klaus Greff, and Jürgen Schmidhuber · 2015
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Going deeper with convolutions
Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich · 2015
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Opening the black box: Revealing interpretable sequence motifs in kernel-based learning algorithms
Marina M-C Vidovic, Nico Görnitz, Klaus-Robert Müller, Gunnar Rätsch, and Marius Kloft · 2015
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Understanding neural networks through deep visualization
Jason Yosinski, Jeff Clune, Anh Nguyen, Thomas Fuchs, and Hod Lipson · 2015
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Character-level convolutional networks for text classification
Xiang Zhang, Junbo Zhao, and Yann LeCun · 2015
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Jaspar 2016: a major expansion and update of the open-access database of transcription factor binding profiles
Anthony Mathelier, Oriol Fornes, David J Arenillas, Chih-yu Chen, Grégoire Denay, Jessica Lee, Wenqiang Shi, Casper Shyr, Ge Tan, Rebecca Worsley-Hunt, et al · 2015
Cited alongside, same era.
Seqgl identifies context-dependent binding signals in genome-wide regulatory element maps
Manu Setty and Christina S Leslie · 2015
Cited alongside, same era.
Jack Lanchantin, Ritambhara Singh, Zeming Lin, and Yanjun Qi · 2016
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