Math.NET aims to provide a self contained clean framework for symbolic mathematical (Computer Algebra System) and numerical/scientific computations, including a parser and support for linear algebra, complex differential analysis, system solving and more
OpenM++: open source microsimulation platform
OpenM++ is an open source microsimulation platform inspired by and compatible with Modgen. OpenM++, compared to its closed source predecessor Modgen, has advantages like portability, scalability and open source. It is not a copy of Modgen, but a new, functionally equivalent implementation of the publicly available language specification.
* GSA-SNP2 is a successor of GSA-SNP (Nam et al. 2010, NAR web server issue). GSA-SNP2 accepts human GWAS summary data (rs numbers, p-values) or gene-wise p-values (possibly obtained from VEGAS or GATES) and outputs pathway gene sets ‘enriched’ with genes associated with the given phenotype. It also provides both local and global protein interaction networks in the associated pathways. * IMPORTANT NOTE: -> PLEASE MOVE OR MAKE A COPY OF 'DATA' FOLDER INTO YOUR INTENSIVE TEST FOLDER (I.E. LINUX OR MAC OR WINDOWS SPECIFIED FOLDER) TO ALLOW THE PROGRAM TO FIND THE PREDESIGNED DATA. * UPDATE NOTE: -> Mar-7-2018: revise header terms in the output file (all versions) -> Jan-8-2018: minor output format update for all versions -> Apr-3-2017: MacOSX command-line version is added. It also provides the PPI net summarization -> Mar-31-2017: Linux and Windows command-line versions now provide the PPI net summary results (except the net visualization)
BigBang/Horizon is a proteomics data analysis pipeline with focus on the shotgun LC/MSMS workflow.
A Matlab software routine to perform Principal Component Analysis using Covariance, Correlation or Comedian as the criterion. Though, initially developed for experiments related to fretting wear but can be effectively used to interpret experimental data from any field. The attached files contain source code as well as a sample MATLAB (.mat) data file of 13 variables. It could be replaced to the data file of your choice. The code is open source but you are requested to give credits if used. Additionally, it also has some useful functions for exporting and generating publication quality figures for different kind of figures in MATLAB
A Python package for estimating the statistical impact of features
This package let's you compute the statistical impact of features given a scikit-learn estimator. The computation is based on the mean variation of the difference between quantile and original predictions. The impact is reliable for regressors and binary classifiers. Currently, all features must consist only of pure-numerical, non-categorical values.
Python module to track the overall median of a stream of values "on-line" in reasonably efficient fashion.
test *only* 1) nr3, Poisson distribution 2) mixture model
Measurement uncertainties with Python.