Search Results for "mixture"

SMTracker v2.0 is a MATLAB-based graphical user interface (GUI) for automatically quantifying, visualising and managing SMT data via five interactive panels, allowing the user to interactively explore tracking data from several conditions, movies and cells on a track-by- track basis. Diffusion parameters and motion behaviour is analysed by several methods: a) by a Gaussian mixture model ,or b) by using the cumulative probability distribution of square displacements, c) Mean-Squared displacement fits, d) by Jump Distance analysis. It also includes exploratory tools to visualise single trajectories or dynamic heat maps.

...fitGCP is a framework for fitting mixtures of probability distributions to genome coverage profiles. Besides commonly used distributions, fitGCP uses distributions tailored to account for common artifacts. The mixture models are iteratively fitted based on the Expectation-Maximization algorithm. Please find the accompanying paper here: http://dx.doi.org/10.1093/bioinformatics/btt147

...To infer the structure of community-level metabolic interactions, BiomeNet applies a mixed-membership modelling framework to enzyme abundance information. The basic idea is that the mixture components of the model (metabolic reactions, subnetworks, and networks) are shared across all groups (microbiome samples), but the mixture proportions vary from group to group. Through this framework, the model can capture nested structures within the data. BiomeNet is unique in modeling each metagenome sample as a mixture of complex metabolic systems (metabosystems).

...It can search through databases of full-length cDNAs, ESTs or mRNA-seq data. Optional assembly of candidate sequences allows assembly of contigs. It is suited to handling a mixture of EST and mRNA-seq sequence data. It performs batch blast searches, so it is ideal for large multi-gene families. After collecting candidate sequences, it performs sequence alignment and deposits sequences into a fasta sequence file for downstream molecular evolutionary analysis.

MCTIMME is a nonparametric Bayesian computational framework for analyzing microbial time-series data.The current implementation is in Matlab.

GenoTan identifies inherited variation of microsatellite loci from short sequence reads using a discretized Gaussian mixture model combined with a rules-based approach.

ESMERALDA is a development environment for statistical recognizers operating on sequential data (speech, handwriting, biological sequences). It supports continuous density Hidden Markov models, Markov chain (N-gramm) models, and Gaussian mixture models.

BigBang/Horizon is a proteomics data analysis pipeline with focus on the shotgun LC/MSMS workflow.

A straight-forward Java implementation of a mixture model with pluggable mixture functions, e.g. a mixture of Gaussian functions. The number and dimensionality of the mixture functions is not limited. All critical calculations are performed in log-space.