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

Exploiting regulatory heterogeneity to systematically identify enhancers with high accuracy

(2019) Hamutal Arbel 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

PEPred-Suite: improved and robust prediction of therapeutic peptides using adaptive feature representation learning

(2019) Leyi Wei et al.   BIOINFORMATICS

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

(2018) Bin Liu et al.   BIOINFORMATICS

NucPosPred: Predicting species-specific genomic nucleosome positioning via four different modes of general PseKNC

(2018) Cangzhi Jia et al.   JOURNAL OF THEORETICAL BIOLOGY

Exploring sequence-based features for the improved prediction of DNA N4-methylcytosine sites in multiple species

(2018) Leyi Wei et al.   BIOINFORMATICS

Genome-wide Identification and Characterization of Enhancers Across 10 Human Tissues

(2018) Lili Xiong et al.   International Journal of Biological Sciences

Sequence based prediction of enhancer regions from DNA random walk

(2018) Anand Pratap Singh et al.   Scientific Reports

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

Identification of activated enhancers and linked transcription factors in breast, prostate, and kidney tumors by tracing enhancer networks using epigenetic traits

(2016) Suhn Kyong Rhie et al.   Epigenetics & Chromatin

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

Improved short-term load forecasting using bagged neural networks

(2015) A.S. Khwaja et al.   ELECTRIC POWER SYSTEMS RESEARCH

Urban traffic flow forecasting through statistical and neural network bagging ensemble hybrid modeling

(2015) Fabio Moretti et al.   NEUROCOMPUTING

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

(2014) Wei Chen et al.   ANALYTICAL BIOCHEMISTRY

Integrating Diverse Datasets Improves Developmental Enhancer Prediction

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

Enhancers: five essential questions

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

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

(2013) Nisha Rajagopal et al.   PLoS Computational Biology

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

Cost-sensitive boosting neural networks for software defect prediction

(2009) Jun Zheng   EXPERT SYSTEMS WITH APPLICATIONS

Ensemble with neural networks for bankruptcy prediction

(2009) Myoung-Jong Kim et al.   EXPERT SYSTEMS WITH APPLICATIONS

A new boosting algorithm for improved time-series forecasting with recurrent neural networks

(2006) Mohammad Assaad et al.   Information Fusion