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bioc
fabia:FABIA: Factor Analysis for Bicluster Acquisition
Biclustering by "Factor Analysis for Bicluster Acquisition" (FABIA). FABIA is a model-based technique for biclustering, that is clustering rows and columns simultaneously. Biclusters are found by factor analysis where both the factors and the loading matrix are sparse. FABIA is a multiplicative model that extracts linear dependencies between samples and feature patterns. It captures realistic non-Gaussian data distributions with heavy tails as observed in gene expression measurements. FABIA utilizes well understood model selection techniques like the EM algorithm and variational approaches and is embedded into a Bayesian framework. FABIA ranks biclusters according to their information content and separates spurious biclusters from true biclusters. The code is written in C.
Maintained by Andreas Mitterecker. Last updated 5 months ago.
statisticalmethodmicroarraydifferentialexpressionmultiplecomparisonclusteringvisualization
5.84 score 32 scripts 6 dependents
mashroommole
MG1StationaryProbability:Computes Stationary Distribution for M/G/1 Queuing System
The idea of a computational algorithm described in the article by Andronov M. et al. (2022) <https://link.springer.com/chapter/10.1007/978-3-030-92507-9_13>. The purpose of this package is to automate computations for a Markov-Modulated M/G/1 queuing system with alternating Poisson flow of arrivals. It offers a set of functions to calculate various mean indices of the system, including mean flow intensity, mean service busy and idle times, and the system's stationary probability.
Maintained by Olga Zoldaka. Last updated 2 years ago.
2.00 score 1 scripts