Search Results for "python data analysis" - Page 2
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Showing 51 open source projects for "python data analysis"
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PMM-Lab
Predictive Microbial Modeling plug-in for KNIME
PMM-Lab is an open-source extension to the Konstanz Information Miner (KNIME). It consists of three components: • a library of KNIME nodes (called PMM-Lab), • a library of “standard” workflows • an HSQL database.to store experimental data and microbial models. Altogether these components are designed to ease and standardize the statistical analysis of experimental microbial data and the development of predictive microbial models (PMM). Users can apply PMM-Lab to proprietary or public data and create bacterial growth / survival / inactivation models. The framework can easily be extended to other model types, e.g. growth/no-growth boundary models. ... -
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Corbata
CORe microBiome Analysis Tools
Corbata is a set of statistical tools that can be used to analyze the core microbiome across a set of samples. -
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DEAPathways
Differential Expression Analysis for Pathways
This project contains the source code associated with the PLoS Computational Biology publication: "Differential Expression Analysis for Pathways". The paper text can be found here: http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1002967 -
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psignifit is a toolbox to fit psychometric functions and test hypotheses on psychometric data. This is version 3 which will now predominantly support python.
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Chordalysis
Log-linear analysis (data modelling) for high-dimensional data
===== Project moved to https://github.com/fpetitjean/Chordalysis ===== Log-linear analysis is the statistical method used to capture multi-way relationships between variables. However, due to its exponential nature, previous approaches did not allow scale-up to more than a dozen variables. We present here Chordalysis, a log-linear analysis method for big data. Chordalysis exploits recent discoveries in graph theory by representing complex models as compositions of triangular structures, also known as chordal graphs. ... -
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slycat
Web-based data science analysis and visualization platform.
This is Slycat - a web-based data science analysis and visualization platform, created at Sandia National Laboratories. The goal of the Slycat project is to develop processes, tools and techniques to support data science, particularly analysis of large, high-dimensional data. -
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MRA
A general recommender system with basic models and MRA
Multi-categorization Recommendation Adjusting (MRA) is to optimize the results of recommendation based on traditional(basic) recommendation models, through introducing objective category information and taking use of the feature that users always get the habits of preferring certain categories. Besides this, there are two advantages of this improved model: 1) it can be easily applied to any kind of existing recommendation models. And 2) a controller is set in this improved model to provide... -
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Implementation in Python of some of the statistical methods provided by "asurv", the survival analysis software.
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SalStat is a small application for statistical analysis emphasising the sciences and social sciences (particularly Psychology). The project is designed around the user interface which has been designed to be simple to use. Think SPSS, but better!
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Statcato is a Java software application for elementary statistics. Its features include data and graph generation, probability distributions, descriptive statistics, confidence intervals, hypothesis tests, correlation, regression, and analysis of var
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TOPS_CeMM
User Friendly Data Analysis Tool for Interaction Data
TOPS provides the benchtop scientist with a free toolset to analyze, filter and visualize data from functional genomic gene-gene and gene-drug interaction screens with a flexible interface to accommodate various different technologies and analysis algorithms in addition to those already provided here. -
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EnvStats
An R Package for Environmental Statistics
...Also included are numerous built-in data sets from regulatory guidance documents and the environmental statistics literature. EnvStats combined with other R packages (e.g., for spatial analysis) provides the environmental scientist, statistician, researcher, and technician with tools to “get the job done!” -
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DeDAY
MLE survival analysis: Gompertz, Weibull, Logistic and mixed morality.
DeDAY (Demography Data Analyses) is a tool of analyzing demography data. It supports Gompertz, Weibull and Logistic distributions. DeDay also supports mixed mortality models based on these distribution such as the Gompertz-Makeham distribution. Distributions such as Gompertz describes only age-dependent mortality, which increases over time. Mixed mortality models, such as in Gompertz-Makeham distribution, consider a more general case where mortality is consist of both age-dependent and... -
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Myrtle
A simple programmable spreadsheet for learning statistics.
...Myrtle offers a unique bookmarking facility which allows students to create and reuse named references to their favorite cell ranges. This can help students focus attention on the important relationships among particular rows or columns of data. Myrtle's graphics and reporting features allow students to report back to their instructors their mastery of course content. -
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Weibull-based reliability toolkit for R
R package for Weibull analysis on (life-)time observations.
This is a small R package for doing Weibull-based reliability analysis. This R package is now obsolete and has been superseded by 'project Abernethy' on http://r-forge.r-project.org/projects/abernethy/. -
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MCPerm: Monte Carlo SNP permutation
Monte Carlo permutation method for SNP multiple test correlation
MCPerm: A Monte Carlo permutation method for multiple test correlation in case-control association study Traditional permutation (TradPerm) test is an important non-parametric analysis method which can be treated as the gold standard for multiple testing corrections in case-control association study. However, it relies on the original single nucleotide polymorphism (SNP) genotypes and phenotypes data to perform a large number of random shuffles, and thus it is computationally intensive, especially for genome-wide association study (GWAS). ... -
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Statistical models with python using numpy and scipy. Currently covers linear regression (with ordinary, generalized and weighted least squares), robust linear regression, and generalized linear model, discrete models, time series analysis and other statistical methods.
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A collection of compact, powerful programs and functions, written in C, for the analysis and transformation of data. No object or structure dependencies, no fancy interfaces - just good tools.
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The final build of this software now is distributed in R, embedded in "RedeR': an R/Bioconductor package for hierarchical and nested network analysis... more about RedeR: http://bioconductor.org/packages/2.9/bioc/html/RedeR.html
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A population-based method for DNA copy number analysis: recurrent copy number aberration indentification in multiple samples (with no need of single-sample calling). Developed for a quick analysis of high resolution and large population data.
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This project hosts tools used for analysis of Gaussian Mixture Distributions (GMDs) which are used for statistical signal processing. The tools are libraries for implementing GMD operations and programs used to analyze properties of GMDs.
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An R package for detailed inspection and analysis of LCMS data. An R package developed by Sukhdeep Singh at Department of Surgery and Cancer, Imperial College London,UK.
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Stand-alone software tool for the interactive CE analysis of microarray data. The software is a user-friendly and allows on-the-fly study of CE
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This program generates customizable hyper-surfaces (multi-dimensional input and output) and samples data from them to be used further as benchmark for response surface modeling tasks or optimization algorithms.
