Interpretable single-cell transcription factor prediction based on deep learning with attention mechanism

Base-resolution prediction of transcription factor binding signals by a deep learning framework

(2022) Qinhu Zhang et al.   PLoS Computational Biology

Comprehensive analysis of single cell ATAC-seq data with SnapATAC

(2021) Rongxin Fang et al.   Nature Communications

Simple oligonucleotide-based multiplexing of single-cell chromatin accessibility

(2021) Kaile Wang et al.   MOLECULAR CELL

Benchmarking algorithms for gene regulatory network inference from single-cell transcriptomic data

(2020) Aditya Pratapa et al.   NATURE METHODS

Gene regulation inference from single-cell RNA-seq data with linear differential equations and velocity inference

(2020) Pierre-Cyril Aubin-Frankowski et al.   BIOINFORMATICS

Locating transcription factor binding sites by fully convolutional neural network

(2020) Qinhu Zhang et al.   BRIEFINGS IN BIOINFORMATICS

Predicting transcription factor binding in single cells through deep learning

(2020) Laiyi Fu et al.   Science Advances

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

(2019) Daniel Quang et al.   METHODS

Single-cell RNA-seq highlights intra-tumoral heterogeneity and malignant progression in pancreatic ductal adenocarcinoma

(2019) Junya Peng et al.   CELL RESEARCH

Droplet-based combinatorial indexing for massive-scale single-cell chromatin accessibility

(2019) Caleb A. Lareau et al.   NATURE BIOTECHNOLOGY

Deep learning for inferring gene relationships from single-cell expression data

(2019) Ye Yuan et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

The Human Transcription Factors

(2018) Samuel A. Lambert et al.   CELL

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

Single-cell profiling of the developing mouse brain and spinal cord with split-pool barcoding

(2018) Alexander B. Rosenberg et al.   SCIENCE

A geometric approach to characterize the functional identity of single cells

(2018) Shahin Mohammadi et al.   Nature Communications

Pupylation sites prediction with ensemble classification model

(2017) Wenzheng Bao et al.   International Journal of Data Mining and Bioinformatics

SCENIC: single-cell regulatory network inference and clustering

(2017) Sara Aibar et al.   NATURE METHODS

A practical guide to single-cell RNA-sequencing for biomedical research and clinical applications

(2017) Ashraful Haque et al.   Genome Medicine

Predicting Hub Genes Associated with Cervical Cancer through Gene Co-Expression Networks

(2016) Su-Ping Deng et al.   IEEE-ACM Transactions on Computational Biology and Bioinformatics

Tracing haematopoietic stem cell formation at single-cell resolution

(2016) Fan Zhou et al.   NATURE

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

(2016) Daniel Quang et al.   NUCLEIC ACIDS RESEARCH

Single-cell chromatin accessibility reveals principles of regulatory variation

(2015) Jason D. Buenrostro et al.   NATURE

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

(2015) Babak Alipanahi et al.   NATURE BIOTECHNOLOGY

ChIPmentation: fast, robust, low-input ChIP-seq for histones and transcription factors

(2015) Christian Schmidl et al.   NATURE METHODS

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

(2015) Jian Zhou et al.   NATURE METHODS

Evaluation of methods for modeling transcription factor sequence specificity

(2013) Matthew T Weirauch et al.   NATURE BIOTECHNOLOGY

Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position

(2013) Jason D Buenrostro et al.   NATURE METHODS

Fast Computation and Applications of Genome Mappability

(2012) Thomas Derrien et al.   PLoS One