Effective gene expression prediction from sequence by integrating long-range interactions
Published 2021 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Effective gene expression prediction from sequence by integrating long-range interactions
Authors
Keywords
-
Journal
NATURE METHODS
Volume 18, Issue 10, Pages 1196-1203
Publisher
Springer Science and Business Media LLC
Online
2021-10-05
DOI
10.1038/s41592-021-01252-x
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- DNABERT: pre-trained Bidirectional Encoder Representations from Transformers model for DNA-language in genome
- (2021) Yanrong Ji et al. BIOINFORMATICS
- Base-resolution models of transcription-factor binding reveal soft motif syntax
- (2021) Žiga Avsec et al. NATURE GENETICS
- Leveraging supervised learning for functionally informed fine-mapping of cis-eQTLs identifies an additional 20,913 putative causal eQTLs
- (2021) Qingbo S. Wang et al. Nature Communications
- Towards a comprehensive catalogue of validated and target-linked human enhancers
- (2020) Molly Gasperini et al. NATURE REVIEWS GENETICS
- Predicting mRNA Abundance Directly from Genomic Sequence Using Deep Convolutional Neural Networks
- (2020) Vikram Agarwal et al. Cell Reports
- A simple new approach to variable selection in regression, with application to genetic fine mapping
- (2020) Gao Wang et al. JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY
- Expanded encyclopaedias of DNA elements in the human and mouse genomes
- (2020) Jill E. Moore et al. NATURE
- 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
- 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
- A systematic evaluation of the design and context dependencies of massively parallel reporter assays
- (2020) Jason C. Klein et al. NATURE METHODS
- Functionally informed fine-mapping and polygenic localization of complex trait heritability
- (2020) Omer Weissbrod et al. NATURE GENETICS
- A Genome-wide Framework for Mapping Gene Regulation via Cellular Genetic Screens
- (2019) Molly Gasperini et al. CELL
- Integration of Multiple Epigenomic Marks Improves Prediction of Variant Impact in Saturation Mutagenesis Reporter Assay
- (2019) Dustin Shigaki et al. HUMAN MUTATION
- The Kipoi repository accelerates community exchange and reuse of predictive models for genomics
- (2019) Žiga Avsec et al. NATURE BIOTECHNOLOGY
- 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
- Integrating regulatory DNA sequence and gene expression to predict genome-wide chromatin accessibility across cellular contexts
- (2019) Surag Nair et al. BIOINFORMATICS
- Activity-by-contact model of enhancer–promoter regulation from thousands of CRISPR perturbations
- (2019) Charles P. Fulco et al. NATURE GENETICS
- Saturation mutagenesis of twenty disease-associated regulatory elements at single base-pair resolution
- (2019) Martin Kircher et al. Nature Communications
- Sequential regulatory activity prediction across chromosomes with convolutional neural networks
- (2018) David R. Kelley et al. GENOME RESEARCH
- Deep learning sequence-based ab initio prediction of variant effects on expression and disease risk
- (2018) Jian Zhou et al. NATURE GENETICS
- Detecting genome-wide directional effects of transcription factor binding on polygenic disease risk
- (2018) Yakir A. Reshef et al. NATURE GENETICS
- CADD: predicting the deleteriousness of variants throughout the human genome
- (2018) Philipp Rentzsch et al. NUCLEIC ACIDS RESEARCH
- gkmSVM: an R package for gapped-kmer SVM
- (2016) Mahmoud Ghandi 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
- Enhancer Evolution across 20 Mammalian Species
- (2015) Diego Villar et al. CELL
- Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning
- (2015) Babak Alipanahi et al. NATURE BIOTECHNOLOGY
- A method to predict the impact of regulatory variants from DNA sequence
- (2015) Dongwon Lee et al. NATURE GENETICS
- Predicting effects of noncoding variants with deep learning–based sequence model
- (2015) Jian Zhou et al. NATURE METHODS
- The selection and function of cell type-specific enhancers
- (2015) Sven Heinz et al. NATURE REVIEWS MOLECULAR CELL BIOLOGY
- A promoter-level mammalian expression atlas
- (2014) NATURE
Become a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get StartedAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started