CT-CBN specifications


Unique identifier OMICS_09056
Alternative name Continuous Time Conjunctive Bayesian Networks
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Programming languages C
License GNU General Public License version 2.0
Computer skills Advanced
Version 0.1.04
Stability Stable
Maintained Yes


No version available


  • person_outline Niko Beerenwinkel

Publications for Continuous Time Conjunctive Bayesian Networks

CT-CBN citations


Progression inference for somatic mutations in cancer

PMCID: 5415494
PMID: 28492066
DOI: 10.1016/j.heliyon.2017.e00277

[…] m mutational events in the human tumor data. The models generated by TO-DAG have been extensively compared with the trees and the graphs inferred by most recent tools representative of the RESIC and CT-CBN . Kang et al. introduced a parametric approach to estimate the sequential order of gene mutations during tumorigenesis from genome sequencing data based on a Markov chain model as TOMC (Tempor […]


Estimating HIV 1 Fitness Characteristics from Cross Sectional Genotype Data

PLoS Comput Biol
PMCID: 4222584
PMID: 25375675
DOI: 10.1371/journal.pcbi.1003886
call_split See protocol

[…] mutations that entered the system of ODEs in the mechanistic model (see Supplementary ). We estimated the mutational scheme from clinical data based on a continuous-time conjunctive Bayesian network (CT-CBN) . The CT-CBN is defined by a partially ordered set (poset) of mutations, denoted by with order relation and by the rate of accumulation (i.e., generation and fixation) of each mutation. The […]

CT-CBN institution(s)
Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland; Department of Mathematics, North Carolina State University, Raleigh, NC, USA

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