ArticleBMC bioinformatics2010
PyMix--the python mixture package--a tool for clustering of heterogeneous biological data.
Article in BMC bioinformatics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Within-patient phylogenetic reconstruction reveals early events in Barrett's Esophagus.Evolutionary applications · 2021Article
- Article
- Expression-based segmentation of the Drosophila genome.BMC genomics · 2013Article
- Predicting gene expression in T cell differentiation from histone modifications and transcription factor binding affinities by linear mixture models.BMC bioinformatics · 2011Article
- Length control of the injectisome needle requires only one molecule of Yop secretion protein P (YscP).Proceedings of the National Academy of Sciences of the United States of America · 2010Article
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Authors and funding
3 authors.
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Abstract
backgroundCluster analysis is an important technique for the exploratory analysis of biological data. Such data is often high-dimensional, inherently noisy and contains outliers. This makes clustering challenging. Mixtures are versatile and powerful statistical models which perform robustly for clustering in the presence of noise and have been successfully applied in a wide range of applications.
resultsPyMix - the Python mixture package implements algorithms and data structures for clustering with basic and advanced mixture models. The advanced models include context-specific independence mixtures, mixtures of dependence trees and semi-supervised learning. PyMix is licenced under the GNU General Public licence (GPL). PyMix has been successfully used for the analysis of biological sequence, complex disease and gene expression data.
conclusionsPyMix is a useful tool for cluster analysis of biological data. Due to the general nature of the framework, PyMix can be applied to a wide range of applications and data sets.
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