Genomics enters the deep learning era

ProteinBERT: a universal deep-learning model of protein sequence and function

(2022) Nadav Brandes et al.   BIOINFORMATICS

Identifying polyadenylation signals with biological embedding via self-attentive gated convolutional highway networks

(2021) Yanbu Guo et al.   APPLIED SOFT COMPUTING

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

(2021) Žiga Avsec et al.   NATURE GENETICS

PlasmidHawk improves lab of origin prediction of engineered plasmids using sequence alignment

(2021) Qi Wang et al.   Nature Communications

Deep learning models predict regulatory variants in pancreatic islets and refine type 2 diabetes association signals

(2020) Agata Wesolowska-Andersen et al.   eLife

Deep Dive into Machine Learning Models for Protein Engineering

(2020) Yuting Xu et al.   Journal of Chemical Information and Modeling

Prediction models for diagnosis and prognosis of covid-19: systematic review and critical appraisal

(2020) Laure Wynants et al.   BMJ-British Medical Journal

Predicting mRNA Abundance Directly from Genomic Sequence Using Deep Convolutional Neural Networks

(2020) Vikram Agarwal et al.   Cell Reports

Cross-species analysis of enhancer logic using deep learning

(2020) Liesbeth Minnoye et al.   GENOME RESEARCH

Genomic analyses implicate noncoding de novo variants in congenital heart disease

(2020) Felix Richter et al.   NATURE GENETICS

Cross-species regulatory sequence activity prediction

(2020) David R. Kelley   PLoS Computational Biology

A Generative Neural Network for Maximizing Fitness and Diversity of Synthetic DNA and Protein Sequences

(2020) Johannes Linder et al.   Cell Systems

Genome annotation across species using deep convolutional neural networks

(2020) Ghazaleh Khodabandelou et al.   PeerJ Computer Science

DeepHPV: a deep learning model to predict human papillomavirus integration sites

(2020) Rui Tian et al.   BRIEFINGS IN BIOINFORMATICS

DeepC: predicting 3D genome folding using megabase-scale transfer learning

(2020) Ron Schwessinger et al.   NATURE METHODS

Predicting 3D genome folding from DNA sequence with Akita

(2020) Geoff Fudenberg et al.   NATURE METHODS

Genome-wide prediction of DNA mutation effect on nucleosome positions for yeast synthetic genomics

(2020) Etienne Routhier et al.   GENOME RESEARCH

Deep learning suggests that gene expression is encoded in all parts of a co-evolving interacting gene regulatory structure

(2020) Jan Zrimec et al.   Nature Communications

Predicting Splicing from Primary Sequence with Deep Learning

(2019) Kishore Jaganathan et al.   CELL

Machine Learning SNP Based Prediction for Precision Medicine

(2019) Daniel Sik Wai Ho et al.   Frontiers in Genetics

FactorNet: a deep learning framework for predicting cell type specific transcription factor binding from nucleotide-resolution sequential data

(2019) Daniel Quang et al.   METHODS

Biological sequence modeling with convolutional kernel networks

(2019) Dexiong Chen et al.   BIOINFORMATICS

DeepPASTA: deep neural network based polyadenylation site analysis

(2019) Ashraful Arefeen et al.   BIOINFORMATICS

Deep learning of the back-splicing code for circular RNA formation

(2019) Jun Wang et al.   BIOINFORMATICS

DeepHistone: a deep learning approach to predicting histone modifications

(2019) Qijin Yin et al.   BMC GENOMICS

DCDE: An Efficient Deep Convolutional Divergence Encoding Method for Human Promoter Recognition

(2019) Wenxuan Xu et al.   IEEE TRANSACTIONS ON NANOBIOSCIENCE

Whole-genome deep-learning analysis identifies contribution of noncoding mutations to autism risk

(2019) Jian Zhou et al.   NATURE GENETICS

Deep learning: new computational modelling techniques for genomics

(2019) Gökcen Eraslan et al.   NATURE REVIEWS GENETICS

Deep Learning in the Biomedical Applications: Recent and Future Status

(2019) Ryad Zemouri et al.   Applied Sciences-Basel

Integrating regulatory DNA sequence and gene expression to predict genome-wide chromatin accessibility across cellular contexts

(2019) Surag Nair et al.   BIOINFORMATICS

Comprehensive evaluation of deep learning architectures for prediction of DNA/RNA sequence binding specificities

(2019) Ameni Trabelsi et al.   BIOINFORMATICS

DeePaC: predicting pathogenic potential of novel DNA with reverse-complement neural networks

(2019) Jakub M Bartoszewicz et al.   BIOINFORMATICS

Integrating distal and proximal information to predict gene expression via a densely connected convolutional neural network

(2019) Wanwen Zeng et al.   BIOINFORMATICS

A Deep Neural Network for Predicting and Engineering Alternative Polyadenylation

(2019) Nicholas Bogard et al.   CELL

Deciphering regulatory DNA sequences and noncoding genetic variants using neural network models of massively parallel reporter assays

(2019) Rajiv Movva et al.   PLoS One

Modeling in-vivo protein-DNA binding by combining multiple-instance learning with a hybrid deep neural network

(2019) Qinhu Zhang et al.   Scientific Reports

DeepSite: bidirectional LSTM and CNN models for predicting DNA–protein binding

(2019) Yongqing Zhang et al.   International Journal of Machine Learning and Cybernetics

Functional interpretation of genetic variants using deep learning predicts impact on chromatin accessibility and histone modification

(2019) Gabriel E Hoffman et al.   NUCLEIC ACIDS RESEARCH

ViraMiner: Deep learning on raw DNA sequences for identifying viral genomes in human samples

(2019) Ardi Tampuu et al.   PLoS One

Expectation pooling: an effective and interpretable pooling method for predicting DNA–protein binding

(2019) Xiao Luo et al.   BIOINFORMATICS

Identifying Cancer-Specific circRNA–RBP Binding Sites Based on Deep Learning

(2019) Zhengfeng Wang et al.   MOLECULES

Technological challenges and milestones for writing genomes

(2019) Nili Ostrov et al.   SCIENCE

TransPrise: a novel machine learning approach for eukaryotic promoter prediction

(2019) Stepan Pachganov et al.   PeerJ

Representation learning of genomic sequence motifs with convolutional neural networks

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

Improving the Quantification of DNA Sequences Using Evolutionary Information Based on Deep Learning

(2019) Hilal Tayara et al.   Cells

Predicting in-vitro Transcription Factor Binding Sites Using DNA Sequence + Shape

(2019) Qinhu Zhang et al.   IEEE-ACM Transactions on Computational Biology and Bioinformatics

GARFIELD-NGS: Genomic vARiants FIltering by dEep Learning moDels in NGS

(2018) Viola Ravasio et al.   BIOINFORMATICS

Inference of the human polyadenylation code

(2018) Michael K K Leung et al.   BIOINFORMATICS

LeNup: learning nucleosome positioning from DNA sequences with improved convolutional neural networks

(2018) Juhua Zhang et al.   BIOINFORMATICS

OUP accepted manuscript

(2018)   BIOINFORMATICS

Sequential regulatory activity prediction across chromosomes with convolutional neural networks

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

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

DeepPolyA: A Convolutional Neural Network Approach for Polyadenylation Site Prediction

(2018) Xin Gao et al.   IEEE Access

DeepSS: Exploring Splice Site Motif Through Convolutional Neural Network Directly From DNA Sequence

(2018) Xiuquan Du et al.   IEEE Access

DeepGSR: an optimized deep-learning structure for the recognition of genomic signals and regions

(2018) Manal Kalkatawi et al.   BIOINFORMATICS

Deep learning in omics: a survey and guideline

(2018) Zhiqiang Zhang et al.   Briefings in Functional Genomics

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

(2018) Marinka Zitnik et al.   Information Fusion

A universal SNP and small-indel variant caller using deep neural networks

(2018) Ryan Poplin et al.   NATURE BIOTECHNOLOGY

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

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

DeepHINT: understanding HIV-1 integration via deep learning with attention

(2018) Hailin Hu et al.   BIOINFORMATICS

An Equivariant Bayesian Convolutional Network predicts recombination hotspots and accurately resolves binding motifs

(2018) Richard Brown et al.   BIOINFORMATICS

Simple tricks of convolutional neural network architectures improve DNA–protein binding prediction

(2018) Zhen Cao et al.   BIOINFORMATICS

Promoter analysis and prediction in the human genome using sequence-based deep learning models

(2018) Ramzan Umarov et al.   BIOINFORMATICS

DeepM6ASeq: prediction and characterization of m6A-containing sequences using deep learning

(2018) Yiqian Zhang et al.   BMC BIOINFORMATICS

Deep learning architectures for prediction of nucleosome positioning from sequences data

(2018) Mattia Di Gangi et al.   BMC BIOINFORMATICS

Prediction of CRISPR sgRNA Activity Using a Deep Convolutional Neural Network

(2018) Li Xue et al.   Journal of Chemical Information and Modeling

A primer on deep learning in genomics

(2018) James Zou et al.   NATURE GENETICS

Deep learning identifies genome-wide DNA binding sites of long noncoding RNAs

(2018) Fan Wang et al.   RNA Biology

Prediction of gene regulatory enhancers across species reveals evolutionarily conserved sequence properties

(2018) Ling Chen et al.   PLoS Computational Biology

CNN-MGP: Convolutional Neural Networks for Metagenomics Gene Prediction

(2018) Amani Al-Ajlan et al.   Interdisciplinary Sciences-Computational Life Sciences

Machine learning for epigenetics and future medical applications

(2017) Lawrence B. Holder et al.   Epigenetics

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

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

N6-methyladenosine (m6A) recruits and repels proteins to regulate mRNA homeostasis

(2017) Raghu R Edupuganti et al.   NATURE STRUCTURAL & MOLECULAR BIOLOGY

Predicting the impact of non-coding variants on DNA methylation

(2017) Haoyang Zeng et al.   NUCLEIC ACIDS RESEARCH

N6-methyladenosine (m6A) recruits and repels proteins to regulate mRNA homeostasis

(2017) Raghu R Edupuganti et al.   NATURE STRUCTURAL & MOLECULAR BIOLOGY

Recognition of prokaryotic and eukaryotic promoters using convolutional deep learning neural networks

(2017) Ramzan Kh. Umarov et al.   PLoS One

Convolutional neural network architectures for predicting DNA–protein binding

(2016) Haoyang Zeng 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

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

(2016) Daniel Quang et al.   NUCLEIC ACIDS RESEARCH

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

The MEME Suite

(2015) Timothy L. Bailey et al.   NUCLEIC ACIDS RESEARCH

Quantitative profiling of initiating ribosomes in vivo

(2014) Xiangwei Gao et al.   NATURE METHODS

A Programmable Dual-RNA-Guided DNA Endonuclease in Adaptive Bacterial Immunity

(2012) M. Jinek et al.   SCIENCE

MEME SUITE: tools for motif discovery and searching

(2009) T. L. Bailey et al.   NUCLEIC ACIDS RESEARCH