A comprehensive revisit of the machine‐learning tools developed for the identification of enhancers in the human genome

Bitter-RF: A random forest machine model for recognizing bitter peptides

(2023) Yu-Fei Zhang et al.   Frontiers in Medicine

iEnhancer-DCSV: Predicting enhancers and their strength based on DenseNet and improved convolutional block attention module

(2023) Jianhua Jia et al.   Frontiers in Genetics

ToxIBTL: prediction of peptide toxicity based on information bottleneck and transfer learning

(2022) Lesong Wei et al.   BIOINFORMATICS

iEnhancer-Deep: A Computational Predictor for Enhancer Sites and Their Strength Using Deep Learning

(2022) Haider Kamran et al.   Applied Sciences-Basel

A sequence-based two-layer predictor for identifying enhancers and their strength through enhanced feature extraction

(2022) Santhosh Amilpur et al.   Journal of Bioinformatics and Computational Biology

A deep learning framework for enhancer prediction using word embedding and sequence generation

(2022) Qitao Geng et al.   BIOPHYSICAL CHEMISTRY

Enhancer-LSTMAtt: A Bi-LSTM and Attention-Based Deep Learning Method for Enhancer Recognition

(2022) Guohua Huang et al.   Biomolecules

SEdb 2.0: a comprehensive super-enhancer database of human and mouse

(2022) Yuezhu Wang et al.   NUCLEIC ACIDS RESEARCH

A machine learning technique for identifying DNA enhancer regions utilizing CIS-regulatory element patterns

(2022) Ahmad Hassan Butt et al.   Scientific Reports

iEnhancer-DCLA: using the original sequence to identify enhancers and their strength based on a deep learning framework

(2022) Meng Liao et al.   BMC BIOINFORMATICS

AcrPred: A hybrid optimization with enumerated machine learning algorithm to predict Anti-CRISPR proteins

(2022) Fu-Ying Dao et al.   INTERNATIONAL JOURNAL OF BIOLOGICAL MACROMOLECULES

iEnhancer-MRBF: Identifying enhancers and their strength with a multiple Laplacian-regularized radial basis function network

(2022) Zhichao Xiao et al.   METHODS

Genome-wide identification and characterization of DNA enhancers with a stacked multivariate fusion framework

(2022) Yansong Wang et al.   PLoS Computational Biology

An Efficient Lightweight Hybrid Model with Attention Mechanism for Enhancer Sequence Recognition

(2022) Suliman Aladhadh et al.   Biomolecules

Prediction of Enhancers in DNA Sequence Data using a Hybrid CNN-DLSTM Model

(2022) Amandeep Kaur et al.   IEEE-ACM Transactions on Computational Biology and Bioinformatics

Enhancer-FRL: Improved and Robust Identification of Enhancers and Their Activities Using Feature Representation Learning

(2022) Chao Wang et al.   IEEE-ACM Transactions on Computational Biology and Bioinformatics

Mechanisms of Enhancer-Promoter Interactions in Higher Eukaryotes

(2021) Olga Kyrchanova et al.   INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES

A transformer architecture based on BERT and 2D convolutional neural network to identify DNA enhancers from sequence information

(2021) Nguyen Quoc Khanh Le et al.   BRIEFINGS IN BIOINFORMATICS

Risk Prediction of Diabetes: Big data mining with fusion of multifarious physical examination indicators

(2021) Hui Yang et al.   Information Fusion

iLearnPlus: a comprehensive and automated machine-learning platform for nucleic acid and protein sequence analysis, prediction and visualization

(2021) Zhen Chen et al.   NUCLEIC ACIDS RESEARCH

DeepCAPE: A Deep Convolutional Neural Network for the Accurate Prediction of Enhancers

(2021) Shengquan Chen et al.   GENOMICS PROTEOMICS & BIOINFORMATICS

ES-ARCNN: Predicting enhancer strength by using data augmentation and residual convolutional neural network

(2021) Ting-He Zhang et al.   ANALYTICAL BIOCHEMISTRY

ATSE: a peptide toxicity predictor by exploiting structural and evolutionary information based on graph neural network and attention mechanism

(2021) Lesong Wei et al.   BRIEFINGS IN BIOINFORMATICS

Transcriptional dysregulation by aberrant enhancer activation and rewiring in cancer

(2021) Atsushi Okabe et al.   CANCER SCIENCE

iEnhancer-RF: Identifying enhancers and their strength by enhanced feature representation using random forest

(2021) Dae Yeong Lim et al.   CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS

iEnhancer-GAN: A Deep Learning Framework in Combination with Word Embedding and Sequence Generative Adversarial Net to Identify Enhancers and Their Strength

(2021) Runtao Yang et al.   INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES

A Novel Position-Specific Encoding Algorithm (SeqPose) of Nucleotide Sequences and Its Application for Detecting Enhancers

(2021) Xuechen Mu et al.   INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES

Enhancers are activated by p300/CBP activity-dependent PIC assembly, RNAPII recruitment, and pause release

(2021) Takeo Narita et al.   MOLECULAR CELL

iEnhancer-EBLSTM: Identifying Enhancers and Strengths by Ensembles of Bidirectional Long Short-Term Memory

(2021) Kun Niu et al.   Frontiers in Genetics

Integrative machine learning framework for the identification of cell-specific enhancers from the human genome

(2021) Shaherin Basith et al.   BRIEFINGS IN BIOINFORMATICS

STALLION: a stacking-based ensemble learning framework for prokaryotic lysine acetylation site prediction

(2021) Shaherin Basith et al.   BRIEFINGS IN BIOINFORMATICS

Genomic enhancers in cardiac development and disease

(2021) Chukwuemeka G. Anene-Nzelu et al.   Nature Reviews Cardiology

Enhancers in disease: molecular basis and emerging treatment strategies

(2021) Annique Claringbould et al.   TRENDS IN MOLECULAR MEDICINE

piEnPred: a bi-layered discriminative model for enhancers and their subtypes via novel cascade multi-level subset feature selection algorithm

(2021) Zaheer Ullah Khan et al.   Frontiers of Computer Science

The dynamic broad epigenetic (H3K4me3, H3K27ac) domain as a mark of essential genes

(2021) Tasnim H. Beacon et al.   Clinical Epigenetics

iEnhancer-RD: Identification of enhancers and their strength using RKPK features and deep neural networks

(2021) Huan Yang et al.   ANALYTICAL BIOCHEMISTRY

A deep learning model to identify gene expression level using cobinding transcription factor signals

(2021) Lirong Zhang et al.   BRIEFINGS IN BIOINFORMATICS

iEnhancer-KL: A Novel Two-Layer Predictor for Identifying Enhancers by Position Specific of Nucleotide Composition

(2021) Yinuo Lyu et al.   IEEE-ACM Transactions on Computational Biology and Bioinformatics

scEnhancer: a single-cell enhancer resource with annotation across hundreds of tissue/cell types in three species

(2021) Tianshun Gao et al.   NUCLEIC ACIDS RESEARCH

BioSeq-BLM: a platform for analyzing DNA, RNA and protein sequences based on biological language models

(2021) Hong-Liang Li et al.   NUCLEIC ACIDS RESEARCH

Analysis of long and short enhancers in melanoma cell states

(2021) David Mauduit et al.   eLife

A Pretraining-Retraining Strategy of Deep Learning Improves Cell-Specific Enhancer Predictions

(2020) Xiaohui Niu et al.   Frontiers in Genetics

CancerEnD: A database of cancer associated enhancers

(2020) Rajesh Kumar et al.   GENOMICS

Isolation and analysis of rereplicated DNA by Rerep-Seq

(2020) Johannes Menzel et al.   NUCLEIC ACIDS RESEARCH

Transcriptional enhancers: from prediction to functional assessment on a genome-wide scale

(2020) Ian C Tobias et al.   GENOME

Enhancer dependence of cell-type–specific gene expression increases with developmental age

(2020) Wenqing Cai et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

iEnhancer-5Step: Identifying enhancers using hidden information of DNA sequences via Chou's 5-step rule and word embedding

(2019) Nguyen Quoc Khanh Le et al.   ANALYTICAL BIOCHEMISTRY

Long-range enhancer–promoter contacts in gene expression control

(2019) Stefan Schoenfelder et al.   NATURE REVIEWS GENETICS

Ensemble of Deep Recurrent Neural Networks for Identifying Enhancers via Dinucleotide Physicochemical Properties

(2019) Tan et al.   Cells

Detect accessible chromatin using ATAC-sequencing, from principle to applications

(2019) Yuanyuan Sun et al.   HEREDITAS

iEnhancer-ECNN: identifying enhancers and their strength using ensembles of convolutional neural networks

(2019) Quang H. Nguyen et al.   BMC GENOMICS

SDM6A: A Web-Based Integrative Machine-Learning Framework for Predicting 6mA Sites in the Rice Genome

(2019) Shaherin Basith et al.   Molecular Therapy-Nucleic Acids

iEnhancer-EL: Identifying enhancers and their strength with ensemble learning approach

(2018) Bin Liu et al.   BIOINFORMATICS

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

(2018) Yifeng Li et al.   BMC BIOINFORMATICS

Enhancer Logic and Mechanics in Development and Disease

(2018) Ryan Rickels et al.   TRENDS IN CELL BIOLOGY

Cicero Predicts cis-Regulatory DNA Interactions from Single-Cell Chromatin Accessibility Data

(2018) Hannah A. Pliner et al.   MOLECULAR CELL

HACER: an atlas of human active enhancers to interpret regulatory variants

(2018) Jing Wang et al.   NUCLEIC ACIDS RESEARCH

mAHTPred: a sequence-based meta-predictor for improving the prediction of anti-hypertensive peptides using effective feature representation

(2018) Balachandran Manavalan et al.   BIOINFORMATICS

Research Progress of Exogenous Plant MiRNAs in Cross-kingdom Regulation

(2018) Hao Zhang et al.   Current Bioinformatics

EnhancerPred2.0: predicting enhancers and their strength based on position-specific trinucleotide propensity and electron–ion interaction potential feature selection

(2017) Wenying He et al.   Molecular BioSystems

DiseaseEnhancer: a resource of human disease-associated enhancer catalog

(2017) Guanxiong Zhang et al.   NUCLEIC ACIDS RESEARCH

HEDD: Human Enhancer Disease Database

(2017) Zhen Wang et al.   NUCLEIC ACIDS RESEARCH

GeneHancer: genome-wide integration of enhancers and target genes in GeneCards

(2017) Simon Fishilevich et al.   Database-The Journal of Biological Databases and Curation

Enhancers and super-enhancers have an equivalent regulatory role in embryonic stem cells through regulation of single or multiple genes

(2016) Sakthi D. Moorthy et al.   GENOME RESEARCH

Transcription factors as readers and effectors of DNA methylation

(2016) Heng Zhu et al.   NATURE REVIEWS GENETICS

iEnhancer-PsedeKNC: Identification of enhancers and their subgroups based on Pseudo degenerate kmer nucleotide composition

(2016) Bin Liu   NEUROCOMPUTING

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

(2016) Feng Liu et al.   Scientific Reports

EP-DNN: A Deep Neural Network-Based Global Enhancer Prediction Algorithm

(2016) Seong Gon Kim et al.   Scientific Reports

EnhancerPred: a predictor for discovering enhancers based on the combination and selection of multiple features

(2016) Cangzhi Jia et al.   Scientific Reports

iEnhancer-2L: a two-layer predictor for identifying enhancers and their strength by pseudok-tuple nucleotide composition

(2015) Bin Liu et al.   BIOINFORMATICS

Progress and challenges in bioinformatics approaches for enhancer identification

(2015) Dimitrios Kleftogiannis et al.   BRIEFINGS IN BIOINFORMATICS

Decoding enhancers using massively parallel reporter assays

(2015) Fumitaka Inoue et al.   GENOMICS

Integrative analysis of 111 reference human epigenomes

(2015) Anshul Kundaje et al.   NATURE

The selection and function of cell type-specific enhancers

(2015) Sven Heinz et al.   NATURE REVIEWS MOLECULAR CELL BIOLOGY

DELTA: A Distal Enhancer Locating Tool Based on AdaBoost Algorithm and Shape Features of Chromatin Modifications

(2015) Yiming Lu et al.   PLoS One

DENdb: database of integrated human enhancers

(2015) Haitham Ashoor et al.   Database-The Journal of Biological Databases and Curation

The Ensembl Regulatory Build

(2015) Daniel R Zerbino et al.   GENOME BIOLOGY

Enhancer Malfunction in Cancer

(2014) Hans-Martin Herz et al.   MOLECULAR CELL

Transcriptional enhancers: from properties to genome-wide predictions

(2014) Daria Shlyueva et al.   NATURE REVIEWS GENETICS

Enhancer biology and enhanceropathies

(2014) Edwin Smith et al.   NATURE STRUCTURAL & MOLECULAR BIOLOGY

DEEP: a general computational framework for predicting enhancers

(2014) Dimitrios Kleftogiannis et al.   NUCLEIC ACIDS RESEARCH

Integrating Diverse Datasets Improves Developmental Enhancer Prediction

(2014) Genevieve D. Erwin et al.   PLoS Computational Biology

Enhanced Regulatory Sequence Prediction Using Gapped k-mer Features

(2014) Mahmoud Ghandi et al.   PLoS Computational Biology

Genome-wide Chromatin State Transitions Associated with Developmental and Environmental Cues

(2013) Jiang Zhu et al.   CELL

Modification of Enhancer Chromatin: What, How, and Why?

(2013) Eliezer Calo et al.   MOLECULAR CELL

kmer-SVM: a web server for identifying predictive regulatory sequence features in genomic data sets

(2013) Christopher Fletez-Brant et al.   NUCLEIC ACIDS RESEARCH

Chromatin stretch enhancer states drive cell-specific gene regulation and harbor human disease risk variants

(2013) S. C. J. Parker et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Genome-Wide Quantitative Enhancer Activity Maps Identified by STARR-seq

(2013) C. D. Arnold et al.   SCIENCE

RFECS: A Random-Forest Based Algorithm for Enhancer Identification from Chromatin State

(2013) Nisha Rajagopal et al.   PLoS Computational Biology

CD-HIT: accelerated for clustering the next-generation sequencing data

(2012) Limin Fu et al.   BIOINFORMATICS

ChromHMM: automating chromatin-state discovery and characterization

(2012) Jason Ernst et al.   NATURE METHODS

Using formaldehyde-assisted isolation of regulatory elements (FAIRE) to isolate active regulatory DNA

(2012) Jeremy M Simon et al.   Nature Protocols

Transcription factors: from enhancer binding to developmental control

(2012) François Spitz et al.   NATURE REVIEWS GENETICS

Genome-wide enhancer prediction from epigenetic signatures using genetic algorithm-optimized support vector machines

(2012) Michael Fernández et al.   NUCLEIC ACIDS RESEARCH

Chromatin signatures of active enhancers

(2012) salvatore spicuglia et al.   Nucleus

Mapping and analysis of chromatin state dynamics in nine human cell types

(2011) Jason Ernst et al.   NATURE

Enhancer function: new insights into the regulation of tissue-specific gene expression

(2011) Chin-Tong Ong et al.   NATURE REVIEWS GENETICS

A User's Guide to the Encyclopedia of DNA Elements (ENCODE)

(2011)   PLOS BIOLOGY

Discover regulatory DNA elements using chromatin signatures and artificial neural network

(2010) Hiram A. Firpi et al.   BIOINFORMATICS

Transcriptional Enhancers in Animal Development and Evolution

(2010) Mike Levine   CURRENT BIOLOGY

Memories of lost enhancers

(2010) R. Sen et al.   GENES & DEVELOPMENT

A unique chromatin signature uncovers early developmental enhancers in humans

(2010) Alvaro Rada-Iglesias et al.   NATURE

A map of open chromatin in human pancreatic islets

(2010) Kyle J Gaulton et al.   NATURE GENETICS

Histone modifications at human enhancers reflect global cell-type-specific gene expression

(2009) Nathaniel D. Heintzman et al.   NATURE

ChIP-seq accurately predicts tissue-specific activity of enhancers

(2009) Axel Visel et al.   NATURE

ChIP–seq: advantages and challenges of a maturing technology

(2009) Peter J. Park   NATURE REVIEWS GENETICS

Discovery and Annotation of Functional Chromatin Signatures in the Human Genome

(2009) Gary Hon et al.   PLoS Computational Biology

High-Resolution Mapping and Characterization of Open Chromatin across the Genome

(2008) Alan P. Boyle et al.   CELL

Analysis and synthesis of high-amplitude Cis-elements in the mammalian circadian clock

(2008) Y. Kumaki et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA