Deep learning: new computational modelling techniques for genomics

Predicting Splicing from Primary Sequence with Deep Learning

(2019) Kishore Jaganathan et al.   CELL

Single-cell RNA-seq denoising using a deep count autoencoder

(2019) Gökcen Eraslan et al.   Nature Communications

pysster: classification of biological sequences by learning sequence and structure motifs with convolutional neural networks

(2018) Stefan Budach et al.   BIOINFORMATICS

Modeling polypharmacy side effects with graph convolutional networks

(2018) Marinka Zitnik et al.   BIOINFORMATICS

OUP accepted manuscript

(2018)   BIOINFORMATICS

Genome-wide prediction of cis-regulatory regions using supervised deep learning methods

(2018) Yifeng Li et al.   BMC BIOINFORMATICS

Prediction of RNA-protein sequence and structure binding preferences using deep convolutional and recurrent neural networks

(2018) Xiaoyong Pan et al.   BMC GENOMICS

Sequential regulatory activity prediction across chromosomes with convolutional neural networks

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

Opportunities and obstacles for deep learning in biology and medicine

(2018) Travers Ching et al.   Journal of the Royal Society Interface

How artificial intelligence is changing drug discovery

(2018) Nic Fleming   NATURE

Deep learning improves prediction of CRISPR–Cpf1 guide RNA activity

(2018) Hui Kwon Kim et al.   NATURE BIOTECHNOLOGY

Deep learning sequence-based ab initio prediction of variant effects on expression and disease risk

(2018) Jian Zhou et al.   NATURE GENETICS

Predicting the clinical impact of human mutation with deep neural networks

(2018) Laksshman Sundaram et al.   NATURE GENETICS

Spatial transcriptomics

(2018) Tal Nawy   NATURE METHODS

Using deep learning to model the hierarchical structure and function of a cell

(2018) Jianzhu Ma et al.   NATURE METHODS

DeFine: deep convolutional neural networks accurately quantify intensities of transcription factor-DNA binding and facilitate evaluation of functional non-coding variants

(2018) Meng Wang et al.   NUCLEIC ACIDS RESEARCH

Deep learning in pharmacogenomics: from gene regulation to patient stratification

(2018) Alexandr A Kalinin et al.   PHARMACOGENOMICS

Enhancing Hi-C data resolution with deep convolutional neural network HiCPlus

(2018) Yan Zhang et al.   Nature Communications

Interpretable dimensionality reduction of single cell transcriptome data with deep generative models

(2018) Jiarui Ding et al.   Nature Communications

Generalizable and Scalable Visualization of Single-Cell Data Using Neural Networks

(2018) Hyunghoon Cho et al.   Cell Systems

Machine Learning for Integrating Data in Biology and Medicine: Principles, Practice, and Opportunities

(2018) Marinka Zitnik et al.   Information Fusion

Deep learning in biomedicine

(2018) Michael Wainberg et al.   NATURE BIOTECHNOLOGY

Deep learning to predict the lab-of-origin of engineered DNA

(2018) Alec A. K. Nielsen et al.   Nature Communications

OUTRIDER: A Statistical Method for Detecting Aberrantly Expressed Genes in RNA Sequencing Data

(2018) Felix Brechtmann et al.   AMERICAN JOURNAL OF HUMAN GENETICS

A primer on deep learning in genomics

(2018) James Zou et al.   NATURE GENETICS

Deep generative modeling for single-cell transcriptomics

(2018) Romain Lopez et al.   NATURE METHODS

AutoImpute: Autoencoder based imputation of single-cell RNA-seq data

(2018) Divyanshu Talwar et al.   Scientific Reports

VASC: Dimension Reduction and Visualization of Single-cell RNA-seq Data by Deep Variational Autoencoder

(2018) Dongfang Wang et al.   GENOMICS PROTEOMICS & BIOINFORMATICS

Deep learning of the regulatory grammar of yeast 5′ untranslated regions from 500,000 random sequences

(2017) Josh T. Cuperus et al.   GENOME RESEARCH

Dermatologist-level classification of skin cancer with deep neural networks

(2017) Andre Esteva et al.   NATURE

Predicting the impact of non-coding variants on DNA methylation

(2017) Haoyang Zeng et al.   NUCLEIC ACIDS RESEARCH

Using neural networks for reducing the dimensions of single-cell RNA-Seq data

(2017) Chieh Lin et al.   NUCLEIC ACIDS RESEARCH

Reconstructing cell cycle and disease progression using deep learning

(2017) Philipp Eulenberg et al.   Nature Communications

The Human Cell Atlas

(2017) Aviv Regev et al.   eLife

Unsupervised Extraction of Stable Expression Signatures from Public Compendia with an Ensemble of Neural Networks

(2017) Jie Tan et al.   Cell Systems

DeepNano: Deep recurrent neural networks for base calling in MinION nanopore reads

(2017) Vladimír Boža et al.   PLoS One

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

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

MiRTDL: A Deep Learning Approach for miRNA Target Prediction

(2016) Shuang Cheng et al.   IEEE-ACM Transactions on Computational Biology and Bioinformatics

Molecular graph convolutions: moving beyond fingerprints

(2016) Steven Kearnes et al.   JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN

Deep learning for computational biology

(2016) Christof Angermueller et al.   Molecular Systems Biology

Classification evaluation

(2016) Jake Lever 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

Taking the Human Out of the Loop: A Review of Bayesian Optimization

(2016) Bobak Shahriari et al.   PROCEEDINGS OF THE IEEE

PEDLA: predicting enhancers with a deep learning-based algorithmic framework

(2016) Feng Liu et al.   Scientific Reports

ADAGE-Based Integration of Publicly Available Pseudomonas aeruginosa Gene Expression Data with Denoising Autoencoders Illuminates Microbe-Host Interactions

(2016) Jie Tan et al.   mSystems

Deep convolutional neural networks for annotating gene expression patterns in the mouse brain

(2015) Tao Zeng et al.   BMC BIOINFORMATICS

Deep learning

(2015) Yann LeCun 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

Machine learning applications in genetics and genomics

(2015) Maxwell W. Libbrecht et al.   NATURE REVIEWS GENETICS

Deep learning in neural networks: An overview

(2015) Jürgen Schmidhuber   NEURAL NETWORKS

DANN: a deep learning approach for annotating the pathogenicity of genetic variants

(2014) Daniel Quang et al.   BIOINFORMATICS

A first look at the Oxford Nanopore MinION sequencer

(2014) Alexander S. Mikheyev et al.   Molecular Ecology Resources

The human splicing code reveals new insights into the genetic determinants of disease

(2014) H. Y. Xiong et al.   SCIENCE

Enhanced Regulatory Sequence Prediction Using Gapped k-mer Features

(2014) Mahmoud Ghandi et al.   PLoS Computational Biology

Evaluation of methods for modeling transcription factor sequence specificity

(2013) Matthew T Weirauch et al.   NATURE BIOTECHNOLOGY

Integrative approaches for finding modular structure in biological networks

(2013) Koyel Mitra et al.   NATURE REVIEWS GENETICS

An integrated encyclopedia of DNA elements in the human genome

(2012)   NATURE

Systematic Localization of Common Disease-Associated Variation in Regulatory DNA

(2012) M. T. Maurano et al.   SCIENCE

Discriminative prediction of mammalian enhancers from DNA sequence

(2011) D. Lee et al.   GENOME RESEARCH

Network medicine: a network-based approach to human disease

(2010) Albert-László Barabási et al.   NATURE REVIEWS GENETICS

Object Detection with Discriminatively Trained Part-Based Models

(2009) P F Felzenszwalb et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

ChIP–seq: advantages and challenges of a maturing technology

(2009) Peter J. Park   NATURE REVIEWS GENETICS

The Graph Neural Network Model

(2008) F. Scarselli et al.   IEEE TRANSACTIONS ON NEURAL NETWORKS