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

CSTP 1.0 – Condition-specific Target Prediction from Motifs and Expression

CSTP 1.0

:: DESCRIPTION

CSTP is a computational tool to predict the TF-target regulation with expression data based on a philosophy of guilt by association. Different from other tools, CSTP does not insist on clear TF binding site in the promoters of target genes.The expression information of genes allows prediction of CSTP to be condition-specific or tissue-specific

::DEVELOPER

Department Computational Molecular Biology, Max Planck Institute for Molecular Genetics

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

Bioinformatics. 2014 Feb 27
Condition-specific target prediction from motifs and expression.
Meng G1, Vingron M.

ExomeCopy 1.32.0 – Copy Number Variant Detection from Exome Sequencing Read Depth

ExomeCopy 1.32.0

:: DESCRIPTION

ExomeCopy implements a hidden Markov model which uses positional covariates, such as background read depth and GC-content, to simultaneously normalize and segment the samples into regions of constant copy count.

::DEVELOPER

Department Computational Molecular Biology, Max-Planck-Institute for Molecular Genetics

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/ Windows/ MacOsX
  • R package
  • BioConductor

:: DOWNLOAD

 ExomeCopy

:: MORE INFORMATION

Citation

Stat Appl Genet Mol Biol. 2011 Nov 8;10(1).
Modeling read counts for CNV detection in exome sequencing data.
Love MI, Myšičková A, Sun R, Kalscheuer V, Vingron M, Haas SA.

PASTAA – Detecting Transcriptions Factors Associated with Functional Categories

PASTAA

:: DESCRIPTION

PASTAA is a software for detecting transcriptions factors associated with functional categories, which utilizes the prediction of binding affinities of a TF to promoters. This binding strength information is compared to the likelihood of membership of the corresponding genes in the functional category under study. Coherence between the two ranked datasets is seen as an indicator of association between a TF and the category. PASTAA is applied primarily to the determination of TFs driving tissue-specific expression.

::DEVELOPER

the Computational Molecular Biology Department at the Max Planck Institute for Molecular Genetics in Berlin, Germany.

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • C++ compiler

:: DOWNLOAD

 PASTAA

:: MORE INFORMATION

Citation

Helge G. Roider*, Thomas Manke, Sean O’Keeffe, Martin Vingron and Stefan A. Haas
PASTAA: identifying transcription factors associated with sets of co-regulated genes
Bioinformatics (2009) 25 (4): 435-442.

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.

CCmiR – Prediction of miRNA Competitive / Cooperative Binding

CCmiR

:: DESCRIPTION

CCmiR is a software for competitive and cooperative microRNA binding prediction

::DEVELOPER

Hu Lab – Data Integration and Knowledge Discovery @ UCF

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows

:: DOWNLOAD

CCmiR

:: MORE INFORMATION

Citation:

Bioinformatics. 2018 Jan 15;34(2):198-206. doi: 10.1093/bioinformatics/btx606.
CCmiR: a computational approach for competitive and cooperative microRNA binding prediction.
Ding J, Li X, Hu H.

PAnalyzer 1.1 – Protein Inference in Shotgun Proteomics

PAnalyzer 1.1

:: DESCRIPTION

PAnalyzer is a software tool focused on the protein inference process of shotgun proteomics.

::DEVELOPER

EhuBio

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows/ MacOsX

:: DOWNLOAD

 PAnalyzer

:: MORE INFORMATION

Citation:

Prieto G, Aloria K, Osinalde N, Fullaondo A, Arizmendi JM, Matthiesen R:
PAnalyzer: A software tool for protein inference in shotgun proteomics.
BMC bioinformatics 2012, 13:288.

Wregex 2.1 – Amino Acid Motif searching

Wregex 2.1

:: DESCRIPTION

Wregex (weighted regular expression).is a software tool for amino acid motif searching.

::DEVELOPER

EhuBio

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 Wregex

:: MORE INFORMATION

Citation:

Bioinformatics. 2014 May 1;30(9):1220-7. doi: 10.1093/bioinformatics/btu016. Epub 2014 Jan 9.
Prediction of nuclear export signals using weighted regular expressions (Wregex).
Prieto G1, Fullaondo A, Rodriguez JA.

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.

ChIPModule 20130227 – Systematic discovery of Transcription Factors and their Cofactors from ChIP-seq data

ChIPModule 20130227

:: DESCRIPTION

ChIPModule is a software tool for systematical discoveray of transcription factors and their cofactors from ChIP-seq data. Given a ChIP-seq dataset and motifs of a large number of transcription factors, ChIPModule can efficiently identify groups of motifs,whose instances significantly co-occur in the ChIP-seq peak regions.

::DEVELOPER

Hu Lab – Data Integration and Knowledge Discovery @ UCF

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/ Windows / MacOsX
  • Python

:: DOWNLOAD

 ChIPModule

:: MORE INFORMATION

Citation:

Pac Symp Biocomput. 2013:320-31.
ChIPModule: systematic discovery of transcription factors and their cofactors from ChIP-seq data.
Ding J, Cai X, Wang Y, Hu H, Li X.