Search Results for "set"

EigenMS is a normalization method implemented in R (and older version in Matlab) available as a set of two functions that should be used in a sequence. Please download EigenMS.zip file (latest version). Latest version uploaded in October 2017 has a bugfix for single treatment group normalization. Rescaling has been omitted from 2015. EigenMS utilizes SVD to detect bias trends in the data and eliminates them. EigenMS eliminates effects from known and unknown factors and can be utilized for any -omic platform. ...

AK Toolbox is a Matlab Toolbox for co-evolution analysis for protein Multiple Sequence Alignment (MSA) distributed under Simplified BSD License. The aim of AK toolbox is to provide a set of Matlab functions, which are independent of Matlab Bioinforamtics Toolbox, for coevolution anaylsis for MSA. At present, co-evolution methods available in this package are Statistical Coupling Analysis (SCA), Explicit Likelihood of Subset Covariance (ELSC), Mutual Information (MI), Observed Minus Expected Square method (OMES), McLanhlan Based Substitution Correlation (MCBASC), Direct-coupling analysis (DCA) and logR. ...

PALM is a software that conducts gene-based association analysis. PALM exploits Hidden Markov Models (HMM) to capture the inner genomic structures. Then, unique gene features (termed "palm prints") are extracted for each gene set by calculating the natural gradient. Then palm-prints are tested with chi-square significance test.

The NAIL (Network Analysis and Inference Library) project is a set of tools for solving problems in the life sciences using network (graph) approaches. NAIL includes methods for creating networks, analysing and comparing networks, and for visualising or presenting the results. These methods are designed as self-contained platform-independent components which can be called either from another program, or from a command line.

...They reflect comorbid neural injury or cerebral vascular disease burden. Their precise detection is of interest in Alzheimer’s disease (AD) with regard to its prognosis. Our toolbox provides a self-sufficient set of tools for segmenting these WMHs reliably and further quantifying their burden for down-processing studies.

KYM is a MATLAB / GNU Octave set of functions that implements a wavelet-based automated procedure of quantification and characterization of biological signals. In particular it has been thought for the analysis of the oscillatory component of cytosolic calcium concentration time course.

This project is designed to explore cancer-related genes from gene expression data set

CRUMp is based on a kernel-based learning method called Classification Relevance Units Machine (CRUM). Given an input set of protein sequences in FASTA format, the system outputs the position, residue type (S, T, or Y), and the estimated probability of each tested site being phosphorylatable. Latest downloadable files: - crump-0.2.0.tar.gz: CRUMp GNU Octave package - crump-0.2.0.zip: CRUMp MATLAB script - crumptestset.fasta: A testing dataset in FASTA format.

Implematation of robust depth-based inference tools for microarray data (a scale curve, to measure the dispersion of a set of curves, a rank test to decide if two groups of curves come from the same population, and classification techniques).

AutoSmooth is a compiled stand-alone graphical interface for signal and derivative extraction from time series with nonstationary noise structure. AutoSmooth is now part of the Signal Extraction Toolbox (SET).