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

Cancer Diagnosis and Disease Gene Identification via Statistical Machine Learning

(2020) Liuyuan Chen et al.   Current Bioinformatics

Boosted K-nearest neighbor classifiers based on fuzzy granules

(2020) Wei Li et al.   KNOWLEDGE-BASED SYSTEMS

Robust Transcription Factor Binding Site Prediction Using Deep Neural Networks

(2020) Kanu Geete et al.   Current Bioinformatics

ACEP: improving antimicrobial peptides recognition through automatic feature fusion and amino acid embedding

(2020) Haoyi Fu et al.   BMC GENOMICS

Prediction of Oxidoreductase Subfamily Classes Based on RFE-SND-CC-PSSM and Machine Learning Methods

(2019) Fang Yuan et al.   Journal of Bioinformatics and Computational Biology

Accurate classification of membrane protein types based on sequence and evolutionary information using deep learning

(2019) Lei Guo et al.   BMC BIOINFORMATICS

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

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

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

(2018) Bin Liu et al.   BIOINFORMATICS

High-Order Convolutional Neural Network Architecture for Predicting DNA-Protein Binding Sites

(2018) Qinhu Zhang et al.   IEEE-ACM Transactions on Computational Biology and Bioinformatics

A Novel Modeling in Mathematical Biology for Classification of Signal Peptides

(2018) Asma Ehsan 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

Varying levels of complexity in transcription factor binding motifs

(2015) Jens Keilwagen et al.   NUCLEIC ACIDS RESEARCH

PseKNC: A flexible web server for generating pseudo K-tuple nucleotide composition

(2014) Wei Chen et al.   ANALYTICAL BIOCHEMISTRY

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

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

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

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

(2013) Nisha Rajagopal et al.   PLoS Computational Biology

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

(2012) Michael Fernández et al.   NUCLEIC ACIDS RESEARCH

Discriminative prediction of mammalian enhancers from DNA sequence

(2011) D. Lee et al.   GENOME RESEARCH

Discover regulatory DNA elements using chromatin signatures and artificial neural network

(2010) Hiram A. Firpi et al.   BIOINFORMATICS

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

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

Finding distal regulatory elements in the human genome

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

ChIP-seq accurately predicts tissue-specific activity of enhancers

(2009) Axel Visel et al.   NATURE