icbn 0.2-13 – Isotonic regression Conjunctive Bayesian Network models

icbn 0.2-13

:: DESCRIPTION

The R package icbn implements algorithms for parameter estimation and model selection for Isotonic Conjunctive Bayesian Network (I-CBN) models. I-CBNs combine isotonic regression on a partially ordered set with CBNs for estimating order constraints among events. The model has been developed to jointly estimate mutational order constraints among genetic events and a genotype-phenotype mapping (such as a fitness landscape) that is non-decreasing along the lattice of genotypes.

::DEVELOPER

the Computational Biology Group (CBG)

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / Linux / MacOsX
  • R package

:: DOWNLOAD

 icbn

:: MORE INFORMATION

Citation

Beerenwinkel N, Knupfer P, Tresch A (2011).
Learning monotonic genotype-phenotype maps.
Stat Appl Genet Mol Biol, Vol. 10, Iss. 1, Art. 3.

PredictPA – A Bayesian Network Model to predict Protein Abundance

PredictPA

:: DESCRIPTION

PredictPA is a Bayesian network model that integrates genomic, transcriptomic and proteomic data to predict protein abundance. Specifically, by using expression, sequence and interaction data, we effectively link transcriptional information with post-transcriptional and protein translational data.

::DEVELOPER

PredictPA team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/MacOsX/Windows
  • MatLab

:: DOWNLOAD

PredictPA

:: MORE INFORMATION

Citation

Ahmed M. Mehdi, Ralph Patrick, Timothy L. Bailey and Mikael Boden (2014),
Predicting the Dynamics of Protein Abundance“,
Molecular and Cellular Proteomics. 13(5): 1330-1340.