MULSEA – Mutual enrichment in aggregated ranked lists

MULSEA

:: DESCRIPTION

MULSEA (MUlti-list SElection algorithm) is a tool for identifying mutual enrichment in aggregated ranked lists with applications to gene expression regulation.

::DEVELOPER

Yakhini Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows

:: DOWNLOAD

MULSEA

:: MORE INFORMATION

Citation

Bioinformatics. 2016 Sep 1;32(17):i464-i472. doi: 10.1093/bioinformatics/btw435.
Mutual enrichment in aggregated ranked lists with applications to gene expression regulation.
Cohn-Alperovich D, Rabner A, Kifer I, Mandel-Gutfreund Y, Yakhini Z.

ARTO – Analysis of Replication Timing and Organization

ARTO

:: DESCRIPTION

ARTO (Analysis of Replication Timing and Organization) uses signal processing methods to fit a constant piece-wise linear curve to the measured raw data. The software takes raw time of replication (ToR) measurement signals as input and outputs for each genomic location an estimate of its ToR and an association to CTR (constant ToR region) or TTR (Temporal Transition Region).

::DEVELOPER

Laboratory of Computational Biology at the Technion.

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/Linux/MacOsX
  • MatLab

:: DOWNLOAD

  ARTO

:: MORE INFORMATION

Citation

Systematic determination of replication activity type highlights interconnections between replication, chromatin structure and nuclear localization.
Farkash-Amar S, David Y, Polten A, Hezroni H, Eldar YC, Meshorer E, Yakhini Z, Simon I.
PLoS One. 2012;7(11):e48986.

QuateXelero – Fast Motif Detection algorithm

QuateXelero

:: DESCRIPTION

QuateXelero is an extremely fast motif detection algorithm which has a Quaternary Tree data structure in the heart.

::DEVELOPER

Laboratory of Systems Biology & Bioinformatics (LBB)

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/ Windows

:: DOWNLOAD

 QuateXelero

:: MORE INFORMATION

Citation

PLoS One. 2013 Jul 18;8(7):e68073. doi: 10.1371/journal.pone.0068073. Print 2013.
QuateXelero: an accelerated exact network motif detection algorithm.
Khakabimamaghani S1, Sharafuddin I, Dichter N, Koch I, Masoudi-Nejad A.

MyMRM 1.2 – Designing Targeted Proteomics Methods

MyMRM 1.2

:: DESCRIPTION

MyMRM is a simple software tool to aid proteomic laboratories designing targeted proteomics methods for their own equipment by using the data of their shotgun experiments.

::DEVELOPER

EhuBio

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows
  • Web Server

:: DOWNLOAD

MyMRM

:: MORE INFORMATION

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.

ChromSDE 2.2 – Inference of Spatial Organizations of Chromosomes Using Semi-definite Embedding Approach and Hi-C Data

ChromSDE 2.2

:: DESCRIPTION

ChromSDE is a deterministic method , which applies semi-definite programming techniques to find the best structure fitting the observed data and uses golden section search to find the correct parameter for converting the contact frequency to spatial distance.

::DEVELOPER

Sung Wing Kin, Ken

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows
  • MatLab

:: DOWNLOAD

ChromSDE

:: MORE INFORMATION

Citation

J Comput Biol. 2013 Nov;20(11):831-46. doi: 10.1089/cmb.2013.0076.
3D chromosome modeling with semi-definite programming and Hi-C data.
Zhang Z, Li G, Toh KC, Sung WK.

BATVI 1.03 – Determine Viral Integrations

BATVI 1.03

:: DESCRIPTION

BatVI is a fast and sensitive method to determine viral integrations.

::DEVELOPER

Sung Wing Kin, Ken

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

BatVI

:: MORE INFORMATION

Citation

BMC Bioinformatics. 2017 Mar 14;18(Suppl 3):71. doi: 10.1186/s12859-017-1470-x.
BATVI: Fast, sensitive and accurate detection of virus integrations.
Tennakoon C, Sung WK.

ChromSDE 2.2 – Inference of Spatial Organizations of Chromosomes Using Semi-definite Embedding Approach and Hi-C Data

ChromSDE 2.2

:: DESCRIPTION

ChromSDE is a software which applies semi-definite programming techniques to find the best structure fitting the observed data and uses golden section search to find the correct parameter for converting the contact frequency to spatial distance.

::DEVELOPER

Sung Wing Kin, Ken

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/ Windows/ MacOsX
  • Java

:: DOWNLOAD

  ChromSDE

:: MORE INFORMATION

Citation

Inference of Spatial Organizations of Chromosomes Using Semi-definite Embedding Approach and Hi-C Data“,
ZZ.Zhang, GL.Li, KC.Toh,and W.Sung,
RECOMB 2013: 317-332

CENTDIST – Discovery of Co-associated Factors by Motif Distribution

CENTDIST

:: DESCRIPTION

CENTDIST is a novel web-application for identifying co-localized transcription factors around ChIP-seq peaks. Unlike traditional motif scanning program, CENTDIST does not require any user-specific parameters and the background. It automatically learns the best set of parameters for different motifs and ranks them based on the skewness of their distribution around ChIP-seq peaks.

::DEVELOPER

Sung Wing Kin, Ken

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web  Browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

Nucleic Acids Res. 2011 Jul;39(Web Server issue):W391-9. doi: 10.1093/nar/gkr387. Epub 2011 May 20.
CENTDIST: discovery of co-associated factors by motif distribution.
Zhang Z1, Chang CW, Goh WL, Sung WK, Cheung E.