iEnhancer-EL / iEnhancer-2L – Identifying Enhancers and their Strength

iEnhancer-EL / iEnhancer-2L

:: DESCRIPTION

iEnhancer-EL is a web server of Identifying enhancers and their strength with ensemble learning approach.

iEnhancer-2L is a two-layer predictor for identifying enhancers and their strength by pseudo k-tuple nucleotide composition

::DEVELOPER

Liu Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Web browser

:: DOWNLOAD

:: MORE INFORMATION

Citation

Liu B, Li K, Huang DS, Chou KC.
iEnhancer-EL: identifying enhancers and their strength with ensemble learning approach.
Bioinformatics. 2018 Nov 15;34(22):3835-3842. doi: 10.1093/bioinformatics/bty458. PMID: 29878118.

Liu B, Fang L, Long R, Lan X, Chou KC.
iEnhancer-2L: a two-layer predictor for identifying enhancers and their strength by pseudo k-tuple nucleotide composition.
Bioinformatics. 2016 Feb 1;32(3):362-9. doi: 10.1093/bioinformatics/btv604. Epub 2015 Oct 17. PMID: 26476782.

iEnhancer-2L – Two-layer predictor for Identifying Enhancers

iEnhancer-2L

:: DESCRIPTION

iEnhancer-2L is a two-layer predictor for identifying enhancers and their strength by pseudo k-tuple nucleotide composition

::DEVELOPER

Liu Lab, Harbin Institute of Technology Shenzhen Graduate School.

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Web browser

:: DOWNLOAD

:: MORE INFORMATION

Citation

iEnhancer-2L: a two-layer predictor for identifying enhancers and their strength by pseudo k-tuple nucleotide composition.
Liu B, Fang L, Long R, Lan X, Chou KC.
Bioinformatics. 2015 Oct 17. pii: btv604.

EPIP – Condition-specific Enhancer–promoter Interaction prediction

EPIP

:: DESCRIPTION

EPIP is a software used to identify target genes of enhancers in human genome. It is a novel computational method to reliably predict EPIs, especially condition-specific ones. EPIP is capable of predicting interactions in samples with limited data as well as in samples with abundant data.

::DEVELOPER

Hu Lab – Data Integration and Knowledge Discovery @ UCF

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux / Windows
Python

:: DOWNLOAD

EPIP

:: MORE INFORMATION

Citation:

Bioinformatics. 2019 Oct 15;35(20):3877-3883. doi: 10.1093/bioinformatics/btz641.
EPIP: a novel approach for condition-specific enhancer-promoter interaction prediction.
Talukder A, Saadat S, Li X, Hu H.

PETModule – Motif Module based approach for Enhancer Target Prediction

PETModule

:: DESCRIPTION

PETModule is a software developed to find enhancer target gene (ETG) pairs through a motif module based approach. The output of the software is the enhancer target gene pairs with a probability score that measures how likely the predicted target gene is reliable. PETModule only needs enhancer locations to predict their target genes.

::DEVELOPER

Hu Lab – Data Integration and Knowledge Discovery @ UCF

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux
Python
Java

:: DOWNLOAD

PETModule

:: MORE INFORMATION

Citation:

Sci Rep. 2016 Jul 20;6:30043. doi: 10.1038/srep30043.
PETModule: a motif module based approach for enhancer target gene prediction.
Zhao C, Li X, Hu H.

PEP – Predict Enhancer Promoter interactions

PEP

:: DESCRIPTION

PEP is a framework for predicting long-range enhancer-promoter interactions (EPI) incorporating two strategies for extracting features directly from the DNA sequences of enhancer and promoter elements

::DEVELOPER

Ma Laboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux / Windows / MacOsX
Python

:: DOWNLOAD

PEP

:: MORE INFORMATION

Citation

Exploiting sequence-based features for predicting enhancer-promoter interactions.
Yang Y, Zhang R, Singh S, Ma J.
Bioinformatics. 2017 Jul 15;33(14):i252-i260. doi: 10.1093/bioinformatics/btx257

FOCS – Analyzing Enhancer and Gene Activity Patterns

FOCS

:: DESCRIPTION

FOCS (FDR-corrected OLS with Cross-validation and Shrinkage) is a resource for enhancer-promoter links based on large-scale high-throughput data

::DEVELOPER

Ron Shamir’s lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Windows/Linux/ MacOsX
R

:: DOWNLOAD

FOCS

:: MORE INFORMATION

Citation

Genome Biol. 2018 May 1;19(1):56. doi: 10.1186/s13059-018-1432-2.
FOCS: a novel method for analyzing enhancer and gene activity patterns infers an extensive enhancer-promoter map.
Hait TA, Amar D, Shamir R, Elkon R.

ESEfinder 3.0 – Exon Splicing Enhancer Finder

ESEfinder 3.0

:: DESCRIPTION

ESEfinder is a web-based resource that facilitates rapid analysis of exon sequences to identify putative ESEs responsive to the human SR proteins SF2/ASF, SC35, SRp40 and SRp55, and to predict whether exonic mutations disrupt such elements.

::DEVELOPER

ESEfinder team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Web Browser

:: DOWNLOAD

:: MORE INFORMATION

Citation

Smith, P. J., Zhang, C., Wang, J. Chew, S. L., Zhang, M. Q. and Krainer, A. R. 2006.
An increased specificity score matrix for the prediction of SF2/ASF-specific exonic splicing enhancers.
Hum. Mol. Genet. 15(16): 2490-2508.

Cartegni L., Wang J., Zhu Z., Zhang M. Q., Krainer A. R.; 2003.
ESEfinder: a web resource to identify exonic splicing enhancers.
Nucleic Acid Research, 2003, 31(13): 3568-3571.

LedPred 1.7.7 – Learning from DNA to Predict enhancers

LedPred 1.7.7

:: DESCRIPTION

LedPred aims at creating a predictive model of regulatory sequences used to score unknown sequences based on the content of DNA motifs, next-generation sequencing (NGS) peaks and signals and other numerical scores of the sequences using supervised classification.

::DEVELOPER

Elodie Darbo, Denis Seyres, Aitor Gonzalez<aitor.gonzalez at univ-amu.fr>

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux/Windows/MacOsX
R/ BioConductor

:: DOWNLOAD

LedPred

:: MORE INFORMATION

Citation:

LedPred: An R/Bioconductor package to predict regulatory sequences using support vector machines.
Seyres D, Darbo E, Perrin L, Herrmann C, González A.
Bioinformatics. 2015 Dec 1. pii: btv705