Global importance analysis: An interpretability method to quantify importance of genomic features in deep neural networks

Base-resolution models of transcription-factor binding reveal soft motif syntax

(2021) Žiga Avsec et al.   NATURE GENETICS

Deep neural networks for interpreting RNA-binding protein target preferences

(2020) Mahsa Ghanbari et al.   GENOME RESEARCH

Predicting Splicing from Primary Sequence with Deep Learning

(2019) Kishore Jaganathan et al.   CELL

Integrating thermodynamic and sequence contexts improves protein-RNA binding prediction

(2019) Yufeng Su et al.   PLoS Computational Biology

Logomaker: beautiful sequence logos in Python

(2019) Ammar Tareen et al.   BIOINFORMATICS

Representation learning of genomic sequence motifs with convolutional neural networks

(2019) Peter K. Koo et al.   PLoS Computational Biology

Provable approximation properties for deep neural networks

(2018) Uri Shaham et al.   APPLIED AND COMPUTATIONAL HARMONIC ANALYSIS

OUP accepted manuscript

(2018)   BIOINFORMATICS

OUP accepted manuscript

(2018)   BIOINFORMATICS

Sequential regulatory activity prediction across chromosomes with convolutional neural networks

(2018) David R. Kelley et al.   GENOME RESEARCH

Comprehensive, high-resolution binding energy landscapes reveal context dependencies of transcription factor binding

(2018) Daniel D. Le et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Maximum entropy methods for extracting the learned features of deep neural networks

(2017) Alex Finnegan et al.   PLoS Computational Biology

Advances and challenges in the detection of transcriptome-wide protein-RNA interactions

(2017) Emily C. Wheeler et al.   Wiley Interdisciplinary Reviews-RNA

RCK: accurate and efficient inference of sequence- and structure-based protein–RNA binding models from RNAcompete data

(2016) Yaron Orenstein et al.   BIOINFORMATICS

Basset: learning the regulatory code of the accessible genome with deep convolutional neural networks

(2016) David R. Kelley et al.   GENOME RESEARCH

Resources for the Comprehensive Discovery of Functional RNA Elements

(2016) Balaji Sundararaman et al.   MOLECULAR CELL

Robust transcriptome-wide discovery of RNA-binding protein binding sites with enhanced CLIP (eCLIP)

(2016) Eric L Van Nostrand et al.   NATURE METHODS

DanQ: a hybrid convolutional and recurrent deep neural network for quantifying the function of DNA sequences

(2016) Daniel Quang et al.   NUCLEIC ACIDS RESEARCH

DNA-dependent formation of transcription factor pairs alters their binding specificity

(2015) Arttu Jolma et al.   NATURE

Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning

(2015) Babak Alipanahi et al.   NATURE BIOTECHNOLOGY

Predicting effects of noncoding variants with deep learning–based sequence model

(2015) Jian Zhou et al.   NATURE METHODS

Design and bioinformatics analysis of genome-wide CLIP experiments

(2015) T. Wang et al.   NUCLEIC ACIDS RESEARCH

RNA Bind-n-Seq: Quantitative Assessment of the Sequence and Structural Binding Specificity of RNA Binding Proteins

(2014) Nicole Lambert et al.   MOLECULAR CELL

Advancing the functional utility of PAR-CLIP by quantifying background binding to mRNAs and lncRNAs

(2014) Matthew B Friedersdorf et al.   GENOME BIOLOGY

GraphProt: modeling binding preferences of RNA-binding proteins

(2014) Daniel Maticzka et al.   GENOME BIOLOGY

DNA-Binding Specificities of Human Transcription Factors

(2013) Arttu Jolma et al.   CELL

Hidden specificity in an apparently nonspecific RNA-binding protein

(2013) Ulf-Peter Guenther et al.   NATURE

A compendium of RNA-binding motifs for decoding gene regulation

(2013) Debashish Ray et al.   NATURE

Evaluation of methods for modeling transcription factor sequence specificity

(2013) Matthew T Weirauch et al.   NATURE BIOTECHNOLOGY

Rbfox proteins regulate alternative mRNA splicing through evolutionarily conserved RNA bridges

(2013) Michael T Lovci et al.   NATURE STRUCTURAL & MOLECULAR BIOLOGY

ViennaRNA Package 2.0

(2011) Ronny Lorenz et al.   Algorithms for Molecular Biology

Transcriptome-wide Identification of RNA-Binding Protein and MicroRNA Target Sites by PAR-CLIP

(2010) Markus Hafner et al.   CELL

iCLIP reveals the function of hnRNP particles in splicing at individual nucleotide resolution

(2010) Julian König et al.   NATURE STRUCTURAL & MOLECULAR BIOLOGY

RNAcontext: A New Method for Learning the Sequence and Structure Binding Preferences of RNA-Binding Proteins

(2010) Hilal Kazan et al.   PLoS Computational Biology

Rapid and systematic analysis of the RNA recognition specificities of RNA-binding proteins

(2009) Debashish Ray et al.   NATURE BIOTECHNOLOGY

HITS-CLIP yields genome-wide insights into brain alternative RNA processing

(2008) Donny D. Licatalosi et al.   NATURE