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

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

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

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

Transcriptional Regulation by (Super)Enhancers: From Discovery to Mechanisms

(2021) Frank Grosveld et al.   Annual Review of Genomics and Human Genetics

IIMLP: integrated information-entropy-based method for LncRNA prediction

(2021) Junyi Li et al.   BMC BIOINFORMATICS

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

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

(2021) Kun Niu et al.   Frontiers in Genetics

Highly accurate protein structure prediction with AlphaFold

(2021) John Jumper et al.   NATURE

Accurate prediction of protein structures and interactions using a three-track neural network

(2021) Minkyung Baek et al.   SCIENCE

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

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

(2021) Huan Yang et al.   ANALYTICAL BIOCHEMISTRY

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

An Information Entropy-Based Approach for Computationally Identifying Histone Lysine Butyrylation

(2020) Guohua Huang et al.   Frontiers in Genetics

im6A-TS-CNN: identifying N6-methyladenine site in multiple tissues by using convolutional neural network

(2020) Kewei Liu et al.   Molecular Therapy-Nucleic Acids

Identification and Classification of Enhancers Using Dimension Reduction Technique and Recurrent Neural Network

(2020) Qingwen Li et al.   Computational and Mathematical Methods in Medicine

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

Bidirectional LSTM with attention mechanism and convolutional layer for text classification

(2019) Gang Liu et al.   NEUROCOMPUTING

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

(2019) Tan et al.   Cells

Identifying enhancer–promoter interactions with neural network based on pre-trained DNA vectors and attention mechanism

(2019) Zengyan Hong et al.   BIOINFORMATICS

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

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

RNAm5CPred: Prediction of RNA 5-Methylcytosine Sites Based on Three Different Kinds of Nucleotide Composition

(2019) Ting Fang et al.   Molecular Therapy-Nucleic Acids

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

(2018) Bin Liu et al.   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

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

(2016) Bin Liu   NEUROCOMPUTING

Exploring Mouse Protein Function via Multiple Approaches

(2016) Guohua Huang et al.   PLoS One

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

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

(2015) Yiming Lu et al.   PLoS One

Transcriptional enhancers: from properties to genome-wide predictions

(2014) Daria Shlyueva et al.   NATURE REVIEWS GENETICS

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

Master Transcription Factors and Mediator Establish Super-Enhancers at Key Cell Identity Genes

(2013) Warren A. Whyte et al.   CELL

Enhancers: five essential questions

(2013) Len A. Pennacchio et al.   NATURE REVIEWS GENETICS

Comparative annotation of functional regions in the human genome using epigenomic data

(2013) Kyoung-Jae Won 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

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

Tissue-specific analysis of chromatin state identifies temporal signatures of enhancer activity during embryonic development

(2012) Stefan Bonn et al.   NATURE GENETICS

ChromHMM: automating chromatin-state discovery and characterization

(2012) Jason Ernst et al.   NATURE METHODS

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

(2012) Michael Fernández et al.   NUCLEIC ACIDS RESEARCH

Computational methods for prediction of protein–RNA interactions

(2011) Tomasz Puton et al.   JOURNAL OF STRUCTURAL BIOLOGY

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

(2011) Jason Ernst et al.   NATURE

Large-scale discovery of enhancers from human heart tissue

(2011) Dalit May et al.   NATURE GENETICS

PU.1 and C/EBP  synergistically program distinct response to NF- B activation through establishing monocyte specific enhancers

(2011) F. Jin et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

CD-HIT Suite: a web server for clustering and comparing biological sequences

(2010) Ying Huang et al.   BIOINFORMATICS

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

High-resolution genome-wide in vivo footprinting of diverse transcription factors in human cells

(2010) A. P. Boyle et al.   GENOME RESEARCH

Widespread transcription at neuronal activity-regulated enhancers

(2010) Tae-Kyung Kim et al.   NATURE

Finding distal regulatory elements in the human genome

(2009) Nathaniel D Heintzman et al.   CURRENT OPINION IN GENETICS & DEVELOPMENT

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

Adaptive Evolution of Pelvic Reduction in Sticklebacks by Recurrent Deletion of a Pitx1 Enhancer

(2009) Y. F. Chan et al.   SCIENCE

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

(2008) Alan P. Boyle et al.   CELL