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GNUexp is a GNUstep/Cocoa framework and a collection of tools helping you to plan, develop, and administer applications associated with visual psychophysics, experimental psychology and statistical data analysis.
Collection of tools for performing robust case-control disease and quantitative trait association studies using Copy Number Variants- Latest version should now be downloaded from Bioconductor
The Life Cycle Assessment Spreadsheet allows you to calculate carbon footprints and other environmental impacts for given product systems. Use requires basic skills in LCA and matrix algebra, but rewards effort with professional analytical tools.
MGARCH is a software library for R-Project to simulate and estimate various MGARCH processes. This project also provides convenience tools for preparing data, summarizing and visualizing results, prediction and documentation.
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).
Structlab is a machine learning C++ framework for structured domains, which provides a toolbox of learning methods and tools for preprocessing and visualization. It also provides a GUI to setup elaborate experiments in a visual and intuitive way.
QRMlib provides a library of methods to investigate Quantitative Risk Management, including Market Risk, Credit Risk and Operational Risk, as developed in the book "Quantitative Risk Management: Concepts, Techniques and Tools".
R Tools for Biologists (RT4Bio) is a multi-functional package writen in R language developed in the Laboratory of Behavioral and Computational Ecology at State University of Montes Claros - MG - Brazil. Formerly known as RRJ.
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Tools to build molecular-docking activity prediction models by PLS regression with iterative training and pose-selection. Descriptors include (i) docking score(s), (ii) pharmacophore features, (iii) multi-feature descriptors learned by decision trees.