BEESEM – Binding Energy Estimation on SELEX with Expectation Maximization

BEESEM

:: DESCRIPTION

The BEESEM program is designed for transcription factor binding motif discovery using HT-SELEX data.

::DEVELOPER

Stormo Lab in Department of Genetics, Washington University

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • Python

:: DOWNLOAD

BEESEM

:: MORE INFORMATION

Citation

Bioinformatics. 2017 Aug 1;33(15):2288-2295. doi: 10.1093/bioinformatics/btx191.
BEESEM: estimation of binding energy models using HT-SELEX data.
Ruan S, Swamidass SJ, Stormo GD

ReMixT v0.5.4 – Clone-specific Genomic Structure Estimation in Cancer

ReMixT v0.5.4

:: DESCRIPTION

ReMixT is a tool for joint inference of clone specific segment and breakpoint copy number in whole genome sequencing data. The input for the tool is a set of segments, a set of breakpoints predicted from the sequencing data, and normal and tumour bam files. Where multiple tumour samples are available, they can be analyzed jointly for additional benefit.

::DEVELOPER

Shah Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / MacOsX / Windows
  • Python

:: DOWNLOAD

ReMixT

:: MORE INFORMATION

Citation

ReMixT: clone-specific genomic structure estimation in cancer.
McPherson AW, Roth A, Ha G, Chauve C, Steif A, de Souza CPE, Eirew P, Bouchard-C?té A, Aparicio S, Sahinalp SC, Shah SP.
Genome Biol. 2017 Jul 27;18(1):140. doi: 10.1186/s13059-017-1267-2.

SPEDRE – Systematic Parameter Estimation in Data-Rich Environments for Cell Signaling Dynamics

SPEDRE

:: DESCRIPTION

SPEDRE is a method for estimating rate constants in a biochemical signaling network, and it is tailored for a special class of data-rich problems with observations of all species — problems that occur mainly when using proteomics technologies such as SILAC.

::DEVELOPER

Lisa Tucker-Kellogg’s Group 

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

Nucleic Acids Res. 2013 Jul;41(Web Server issue):W187-91. doi: 10.1093/nar/gkt459.
SPEDRE: a web server for estimating rate parameters for cell signaling dynamics in data-rich environments.
Nim TH, White JK, Tucker-Kellogg L.

mhsmm 0.4.16 – Parameter Estimation and Prediction for Hidden Markov and semi-Markov models for data with multiple Observation Sequences

mhsmm 0.4.16

:: DESCRIPTION

mhsmm is a software of parameter estimation and prediction for hidden Markov and semi-Markov models for data with multiple observation sequences. The software is suitable for equidistant time series data, with multivariate and/or missing data.

::DEVELOPER

Jared O’Connell and Jonathan Marchini.

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/Windows/MacOsX
  • R package

:: DOWNLOAD

  mhsmm

:: MORE INFORMATION

Citation

Jared O’Connell, Soren Hojsgaard (2011).
Hidden Semi Markov Models for Multiple Observation Sequences: The mhsmm Package for R.
Journal of Statistical Software, 39(4), 1-22.

MPFE 1.8.0 – Estimation of Methylation Pattern Distribution from Deep Sequencing data

MPFE 1.8.0

:: DESCRIPTION

MPFE is an R Bioconductor package for calculation of the estimated distribution over methylation patterns.

::DEVELOPER

Peijie Lin, Sylvain Foret, Conrad Burden <conrad.burden at anu.edu.au>

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / Linux/ MacOsX
  • R
  • BioConductor

:: DOWNLOAD

 MPFE

:: MORE INFORMATION

Citation

Estimation of the methylation pattern distribution from deep sequencing data.
Lin P, Forêt S, Wilson SR, Burden CJ.
BMC Bioinformatics. 2015 May 6;16(1):145.

FastEPRR 1.0 – Fast Estimation of Population Recombination Rates

FastEPRR 1.0

:: DESCRIPTION

FastEPRR is an extremely fast open-source software package to estimate population recombination rate based on intraspecific DNA polymorphism data.

::DEVELOPER

Evolutionary Genomics Lab, PICB

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/Linux
  • R

:: DOWNLOAD

 FastEPRR

:: MORE INFORMATION

Citation

New Software for the Fast Estimation of Population Recombination Rates (FastEPRR) in the Genomic Era.
Gao F, Ming C, Hu W, Li H.
G3 (Bethesda). 2016 Mar 30. pii: g3.116.028233. doi: 10.1534/g3.116.028233

MicrobeCensus 1.0.7 – Average Genome Size Estimation from Shotgun data

MicrobeCensus 1.0.7

:: DESCRIPTION

MicrobeCensus : Rapidly and accurate estimate the average genome size (AGS)

::DEVELOPER

Pollard Group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 MicrobeCensus

:: MORE INFORMATION

stochprofML 1.2 – Stochastic Profiling using Maximum Likelihood Estimation

stochprofML 1.2

:: DESCRIPTION

stochprofML is an R package of parameterizing cell-to-cell regulatory heterogeneities via stochastic transcriptional profiles

::DEVELOPER

Biostatistics, Institute of Computational Biology

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows/ MacOsX
  • R
:: DOWNLOAD

 stochprofML

:: MORE INFORMATION

Citation:

Proc Natl Acad Sci U S A. 2014 Feb 4;111(5):E626-35. doi: 10.1073/pnas.1311647111. Epub 2014 Jan 21.
Parameterizing cell-to-cell regulatory heterogeneities via stochastic transcriptional profiles.
Bajikar SS1, Fuchs C, Roller A, Theis FJ, Janes KA.

REDEMPTION 20150708 – Reduced Dimension Ensemble Modeling and Parameter Estimation

REDEMPTION 20150601

:: DESCRIPTION

REDEMPTION is a MATLAB toolbox for the identification of parameters and parameter ensembles of ODE models from time-series data.

:: DEVELOPER

Chemical and Biological Systems Engineering Laboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / windows/ MacOsX
  • MatLab

:: DOWNLOAD

 REDEMPTION

:: MORE INFORMATION

Citation

REDEMPTION: Reduced Dimension Ensemble Modeling and Parameter Estimation.
Liu Y, Manesso E, Gunawan R.
Bioinformatics. 2015 Jun 14. pii: btv365.

LDhelmet 1.7 – Fine-scale Recombination Rate Estimation

LDhelmet 1.7

:: DESCRIPTION

LDhelmet is a software program for statistical inference of fine-scale crossover recombination rates from population genetic data.

::DEVELOPER

Yun S. Song

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • C++ Compiler

:: DOWNLOAD

 LDhelmet

:: MORE INFORMATION

Citation

Chan, A.H., Jenkins, P.A., and Song, Y.S.
Genome-wide fine-scale recombination rate variation in Drosophila melanogaster.
PLoS Genetics, vol. 8 no. 12 (2012) e1003090.