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PyMix - The Python Mixture package | PyMix / Home

PyMix - The Python mixture package. The Python Mixture Package (PyMix) is a freely available Python library implementing algorithms and data structures for a wide variety of data mining applications with basic and extended mixture models. Features. Finite mixture models of discrete and continuous features. Wide range of available distributions (Normal, Exponential, Discrete, Dirichlet, Normal-Gamma, Uniform, HMM). ML and MAP parameter estimation. Context-specific independence structure learning.

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PyMix - The Python Mixture package | PyMix / Home | pymix.org Reviews
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PyMix - The Python mixture package. The Python Mixture Package (PyMix) is a freely available Python library implementing algorithms and data structures for a wide variety of data mining applications with basic and extended mixture models. Features. Finite mixture models of discrete and continuous features. Wide range of available distributions (Normal, Exponential, Discrete, Dirichlet, Normal-Gamma, Uniform, HMM). ML and MAP parameter estimation. Context-specific independence structure learning.
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PyMix - The Python Mixture package | PyMix / Home | pymix.org Reviews

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PyMix - The Python mixture package. The Python Mixture Package (PyMix) is a freely available Python library implementing algorithms and data structures for a wide variety of data mining applications with basic and extended mixture models. Features. Finite mixture models of discrete and continuous features. Wide range of available distributions (Normal, Exponential, Discrete, Dirichlet, Normal-Gamma, Uniform, HMM). ML and MAP parameter estimation. Context-specific independence structure learning.

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PyMix - The Python Mixture package | PyMix / Home

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PyMix - The Python mixture package. The Python Mixture Package (PyMix) is a freely available Python library implementing algorithms and data structures for a wide variety of data mining applications with basic and extended mixture models. Features. Finite mixture models of discrete and continuous features. Wide range of available distributions (Normal, Exponential, Discrete, Dirichlet, Normal-Gamma, Uniform, HMM). ML and MAP parameter estimation. Context-specific independence structure learning.

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Darr; Skip to Main Content. Sere K., Freitas, J. Zenke, M., Costa, I.G. 2016), Differential Peak Calling of ChIP-seq Signals with Replicates with THOR, Nucleic Acids Research. Epub gkw680 [ paper. Zenke, M., Costa, I.G. 2016), Analysis of computational footprinting methods for DNase sequencing experiments, Nature Methods. 13, 303 309 [ paper. Nascimento, A. C. Prudencio, R.B.C, Costa I.G. A Multiple Kernel Learning algorithm for drug-target interaction prediction, BMC. 51(2):267-270. [ paper. Deary I&#46...

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Darr; Skip to Main Content. Is a toolbox for the integrative analysis of regulatory and expression data from ChIP-Seq, RNA-Seq and biological sequences. The tool provides several functionalities required for regulatory analysis as Chip-Seq peak calling, transcription factor binding site detection and association to further experimental data as gene expression. Provides multiple motif analysis common operations such as motif matching and motif enrichment. All analyses allow experimental flexibility an...

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PyMix - The Python Mixture package | PyMix / Home

PyMix - The Python mixture package. The Python Mixture Package (PyMix) is a freely available Python library implementing algorithms and data structures for a wide variety of data mining applications with basic and extended mixture models. Features. Finite mixture models of discrete and continuous features. Wide range of available distributions (Normal, Exponential, Discrete, Dirichlet, Normal-Gamma, Uniform, HMM). ML and MAP parameter estimation. Context-specific independence structure learning.

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