ArticlePloS one2015
DELTA: A Distal Enhancer Locating Tool Based on AdaBoost Algorithm and Shape Features of Chromatin Modifications.
Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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Who cites it
29 citing papers in PubMed.
- Article
- Pig-eRNAdb: a comprehensive enhancer and eRNA dataset of pigs.Scientific data · 2024Article
- Computational methods for identifying enhancer-promoter interactions.Quantitative biology (Beijing, China) · 2023Review
- iEnhancer-DCSV: Predicting enhancers and their strength based on DenseNet and improved convolutional block attention module.Frontiers in genetics · 2023Article
- Boosting tissue-specific prediction of active cis-regulatory regions through deep learning and Bayesian optimization techniques.BMC bioinformatics · 2022Article
- Accurate prediction of functional states of cis-regulatory modules reveals common epigenetic rules in humans and mice.BMC biology · 2022Article
- Enhancer-LSTMAtt: A Bi-LSTM and Attention-Based Deep Learning Method for Enhancer Recognition.Biomolecules · 2022Article
- Jasmonates and Histone deacetylase 6 activate Arabidopsis genome-wide histone acetylation and methylation during the early acute stress response.BMC biology · 2022Article
- DeepCAPE: A Deep Convolutional Neural Network for the Accurate Prediction of Enhancers.Genomics, proteomics & bioinformatics · 2021Article
- DECODE: a Deep-learning framework for Condensing enhancers and refining boundaries with large-scale functional assays.Bioinformatics (Oxford, England) · 2021Article
- Annotating the Insect Regulatory Genome.Insects · 2021Review
- A pitfall for machine learning methods aiming to predict across cell types.Genome biology · 2020Article
- Supervised enhancer prediction with epigenetic pattern recognition and targeted validation.Nature methods · 2020Article
- A comprehensive review of computational prediction of genome-wide features.Briefings in bioinformatics · 2020Article
- Functional Characterization of a Dual Enhancer/Promoter Regulatory Element Leading HumanFrontiers in genetics · 2020Article
- Deciphering essential cistromes using genome-wide CRISPR screens.Proceedings of the National Academy of Sciences of the United States of America · 2019Article
- Exploiting regulatory heterogeneity to systematically identify enhancers with high accuracy.Proceedings of the National Academy of Sciences of the United States of America · 2019Article
- Beyond the Exome: The Non-coding Genome and Enhancers in Neurodevelopmental Disorders and Malformations of Cortical Development.Frontiers in cellular neuroscience · 2019Article
- Differential analysis of chromatin accessibility and histone modifications for predicting mouse developmental enhancers.Nucleic acids research · 2018Article
- A neural network based model effectively predicts enhancers from clinical ATAC-seq samples.Scientific reports · 2018Article
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4 authors.
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Abstract
Accurate identification of DNA regulatory elements becomes an urgent need in the post-genomic era. Recent genome-wide chromatin states mapping efforts revealed that DNA elements are associated with characteristic chromatin modification signatures, based on which several approaches have been developed to predict transcriptional enhancers. However, their practical application is limited by incomplete extraction of chromatin features and model inconsistency for predicting enhancers across different cell types. To address these issues, we define a set of non-redundant shape features of histone modifications, which shows high consistency across cell types and can greatly reduce the dimensionality of feature vectors. Integrating shape features with a machine-learning algorithm AdaBoost, we developed an enhancer predicting method, DELTA (Distal Enhancer Locating Tool based on AdaBoost). We show that DELTA significantly outperforms current enhancer prediction methods in prediction accuracy on different datasets and can predict enhancers in one cell type using models trained in other cell types without loss of accuracy. Overall, our study presents a novel framework for accurately identifying enhancers from epigenetic data across multiple cell types.
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