3PEAT – Paired-End Analysis of Transcription Start Sites in Arabidopsis Reveals Plant-Specific Promoter Signatures

3PEAT

:: DESCRIPTION

3PEAT (Plant PEAT Peaks) predicts the probability of a TSS at any given nucleotide in the Arabidopsis genome solely from the DNA sequence surrounding that nucleotide.

::DEVELOPER

Megraw Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux

:: DOWNLOAD

3PEAT

:: MORE INFORMATION

Citation

Morton T, Petricka J, Corcoran DL, Li S, Winter CM, Carda A, Benfey PN, Ohler U, Megraw M. (2014).
Paired-end analysis of transcription start sites in Arabidopsis reveals plant-specific promoter signatures.
Plant Cell, 26:2746-60.

HIPPIE 0.0.2b – High-Throughput Identification Pipeline for Promoter Interacting Enhancer elements

HIPPIE 0.0.2b

:: DESCRIPTION

HIPPIE is the workflow for analyzing Hi-C paired-end reads in FASTQ format and predict enhancer–target gene interactions. HIPPIE streamlines the entire processing phase including reads mapping, quality control and enhancer–target gene prediction as well as characterizing the interactions.

::DEVELOPER

Wang Lab @ IBI

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux

:: DOWNLOAD

HIPPIE

:: MORE INFORMATION

Citation

HIPPIE: A high-throughput identification pipeline for promoter interacting enhancer elements.
Hwang YC, Lin CF, Valladares O, Malamon J, Kuksa P, Zheng Q, Gregory BD, Wang LS.
Bioinformatics. 2014 Dec 4. pii: btu801.

Promoter 2.0 – Transcription Start Sites in Vertebrate DNA

Promoter 2.0

:: DESCRIPTION

Promoter predicts transcription start sites of vertebrate PolII promoters in DNA sequences. It has been developed as an evolution of simulated transcription factors that interact with sequences in promoter regions. It builds on principles that are common to neural networks and genetic algorithms.

::DEVELOPER

DTU Health Tech

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux

:: DOWNLOAD

Promoter

:: MORE INFORMATION

Citation

Promoter 2.0: for the recognition of PolII promoter sequences.
Steen Knudsen
Bioinformatics 15, 356-361, 1999.

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.

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

PrimerZ 20171130 – Streamlined Primer design for Promoters, Exons and Human SNPs

PrimerZ 20171130

:: DESCRIPTION

PrimerZ is a web application dedicated primarily to primer design for genes and human SNPs.

::DEVELOPER

PrimerZ team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Web Browser

:: DOWNLOAD

:: MORE INFORMATION

Citation

PrimerZ: streamlined primer design for promoters, exons and human SNPs.
Tsai MF, Lin YJ, Cheng YC, Lee KH, Huang CC, Chen YT, Yao A.
Nucleic Acids Res. 2007 Jul;35(Web Server issue):W63-5. Epub 2007 May 30.

CpGProD – Predict Mammalian Promoters Associated with CpG Islands

CpGProD

:: DESCRIPTION

CpGProD (CpG Island Promoter Detection) is an application for identifying mammalian promoter regions associated with CpG islands in large genomic sequences. Although it is strictly dedicated to this particular promoter class corresponding to ≈50% of the genes, CpGProD exhibits a higher sensitivity and specificity than other tools used for promoter prediction. Notably, CpGProD uses different parameters according to species (human, mouse) studied. Moreover, CpGProD predicts the promoter orientation on the DNA strand.

CpGProD Online Version

::DEVELOPER

PRABI-Doua

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Windows / Mac OsX / Linux

:: DOWNLOAD

CpGProD

:: MORE INFORMATION

Citation

Ponger, L. and Mouchiroud, D. (2001)
CpGProD: identifying CpG islands associated with transcription start sites in large genomic mammalian sequences.
Bioinformatics, 18, 631-633

iProEP – Predictor for Predicting Promoter

iProEP

:: DESCRIPTION

iProEP is a promoter prediction tools of five species: Homo sapiens, Drosophila melanogaster, Caenorhabditis elegans, Bacillus subtilis, and Escherichia coli. The PseKNC and PCSF features were employed to formulate promoter samples.

::DEVELOPER

LinDing Group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Web Browser

:: DOWNLOAD

:: MORE INFORMATION

Citation

iProEP: A Computational Predictor for Predicting Promoter.
Lai HY, Zhang ZY, Su ZD, Su W, Ding H, Chen W, Lin H.
Mol Ther Nucleic Acids. 2019 Sep 6;17:337-346. doi: 10.1016/j.omtn.2019.05.028.

iPro54-PseKNC – Predicting Promoters with Pseudo k-tuple Nucleotide Composition

iPro54-PseKNC

:: DESCRIPTION

iPro54-PseKNC is a sequence-based predictor for identifying σ54 promoters with pseudo k-tuple nucleotide composition

::DEVELOPER

LinDing Group

:: SCREENSHOTS

n/a

:: REQUIREMENTS

Web browser

:: DOWNLOAD

:: MORE INFORMATION

Citation

iPro54-PseKNC: a sequence-based predictor for identifying sigma-54 promoters in prokaryote with pseudo k-tuple nucleotide composition.
Lin H, Deng EZ, Ding H, Chen W, Chou KC.
Nucleic Acids Res. 2014 Dec 1;42(21):12961-72. doi: 10.1093/nar/gku1019

SigmaPromoter 1.0 – Promoter Prediction method based on multiple Sigma Factors model for Bacterial Genomes

SigmaPromoter 1.0

:: DESCRIPTION

SigmaPromoter is a method of providing predictions for four chosen sigma promoters as an attempt to comprehensively characterize and predict non-housekeeping sigma promoters.

::DEVELOPER

ZhuLab, Peking Uiniversity, Beijing

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux/ Windows

:: DOWNLOAD

SigmaPromoter

:: MORE INFORMATION