Open Source S/R Data Management Systems
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S/R Data Management Systems
View 4375 business solutionsBrowse free open source S/R Data Management Systems and projects below. Use the toggles on the left to filter open source S/R Data Management Systems by OS, license, language, programming language, and project status.
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R packages (maintained by YJLEE)
R packages for PK/PD modeling , BE/BA, drug stability, ivivc, etc.
These R packages are developed for data analysis of PK/PD modeling & simulation, bioequivalence/bioavailability (BE/BA), drug stability, in-vitro and in-vivo correlation (ivivc), as well as therapeutic drug monitoring (TDM). -
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Mass-Up
MALDI-TOF data analysis tool
Mass-Up is an Open-Source mass spectrometry utility for proteomics designed to support the preprocessing and analysis of MALDI-TOF mass spectrometry data. Mass-Up includes several tools and operations to load, preprocess and analyze MALDI-TOF data. -
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IAP.G2P
IAP - the Integrated Analysis Pipeline
The Integrated Analysis Platform (IAP) has been designed and developed to support the analysis of large-scale image data sets of different camera systems. It aims in bridging different data domains and in integrating different approaches to data analysis and post-processing. -
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a R package. 'Qair' gives access to data bases used by air quality monitoring associations in France. It also contains functions to manipualte air quality datas.
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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PheMaDB is a web-based data management system to store and analyze OmniLog Phenotype Microarray data. The manuscript can be accessed here: http://www.biomedcentral.com/1471-2105/12/109. Chang WE et al. BMC Bioinformatics. 2011 Apr 20;12(1):109.
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EnvStats
An R Package for Environmental Statistics
EnvStats is an R package for environmental statistics. It is the open-source successor to the commercial module for S-Plus© called "EnvironmentalStats for S-Plus", which was first released in April, 1997. The EnvStats package, along with the R software environment, provides comprehensive and powerful software for environmental data analysis. EnvStats brings the major environmental statistical methods found in the literature and regulatory guidance documents into one statistical package, along with an extensive hypertext help system that explains what these methods do, how to use these methods, and where to find them in the environmental statistics literature. 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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TeachingDemos
Bioinformatics related demos and tutorials using the R programming lan
Bioinformatics related demos and tutorials using the R programming language for large biological data. Licence: Creative Commons Attribution-NonCommercial 4.0 International License -
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iMir
Integrated pipeline for HT miRNA-Seq data analysis
Processing of smallRNA-Seq data to gather biologically relevant information requires application of multiple statistical and bioinformatics tools from different sources, each focusing on a specific step of the analysis pipeline. The analytical workflow can be challenging for the continuous interventions by the operator, a critical factor when large numbers of datasets need to be analyzed at once. To allow a flexible and comprehensive analysis of smallRNA-Seq data we designed a novel modular pipeline, called iMir, integrating multiple open source modules and resource in an automated workflow, devising different statistical approaches to analyze data rigorously. iMir comprises also a Graphical User Interface (GUI), so that the pipeline is particularly suited for biologist and early stage bioinformaticians and produces both graphics and text outputs. -
Cut Data Warehouse Costs by 54%BigQuery delivers 54% lower TCO with exabyte scale and flexible pricing. Free migration tools handle the SQL translation automatically.
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mzMatch is a Java collection of small commandline tools specific for metabolomics MS data analysis. The tools are built on top of the PeakML core library, providing mass spectrometry specific functionality and access to the PeakML file format.
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The Canopy project is an initiative to merge and expand the functionality of Perl-speaks-NONMEM (PsN), Census, Xpose and PopED. The goal is to produce a coherent, inclusive and convenient platform for pharmacometric data analysis.
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Chinese I Ching R Algorithms
Chinese I Ching Algorithms implemented with R programming
I Ching offers an idea to summary the world by constructing functional mappings in finite groups. Much of ancient Chinese natural and social science grew from its concepts as root. The derived theories like "Eight Diagrams", "Five Elements" became the foundation of nearly all academic fields in acient Chinese. As a result, the theories are also the high concentration of many practical and statistical experience in China during her thousands-of-year history. This project tries to realize these algorithms with statistical programming. Overcoming the long span has important meanings. First, we can verify the validity of algorithm with big data. Second, we can put them into unprecedented wide application in the age of data. Third, the unique inspection of I Ching that linked "all the universe" open new eyes for us in thought and methodology about interdisciplinary use of data. This program is open-source for human. If you are interested in it, welcome to discuss and work together. -
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Chipster is a biologist-friendly analysis software for high-throughput data. It contains over 200 analysis tools for next generation sequencing (NGS), microarray and proteomics data. Users can combine tools in automatic analysis workflows, which can be shared. Chipster's interactive visualizations allow users to select datapoints and create new gene lists. For NGS data Chipster contains a built-in genome browser, which highlights SNPs and automatically indexes BAM files and calculates coverage. Chipster’s ability to provide a biologist-friendly access to a powerful analysis platform is technically based on a desktop application user interface, a flexible distributed architecture, and the ability to integrate many types of analysis tools (command line, R/Bioconductor, Java, Web Services etc). The platform is generic and easily extendable to other areas, even beyond bioinformatics. For more information, please see http://chipster.csc.fi and http://genomebiology.com/1471-2164/12/
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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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Django-dataplot enables developers using the Django web framework to seamlessly integrate data-driven graphical plots into their web pages.
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Electrophysiology & circular stats tools
Data analysis and circular statistics with OpenElectrophy and R
Set of tools for basic analysis of electrophysiological data. The Python classes show how to call OpenElectrophy functions and save data. The R library applies circular statistics to spike phase data and saves the best von Mises fit and the Rayleigh statistics on the disk. The wavelet coherence analysis is done in R by the package "sowas". Check the module R_coherence to see how we solved that problem. This packages may be useful for people who start using OpenElectrophy and circular statistics in R. If you find errors, please report them. The project is still in development, so in the future you'll get updates. -
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Open, extensible web-based collaborative platform for microarray gene expression, sequence and PPI data analysis, exposing distinct chainable components for clustering, pattern discovery, statistics (thru R), machine-learning algorithms and visualization
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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.
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Hyperspectral data analysis in R
Handling and basic analysis of hyperspectral data in R
The hsdar package contains classes and functions to manage, analyse and simulate hyperspectral data. These might be either spectrometer measurements or hyperspectral images through the interface of rgdal. -
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Maui
Maui is the Maltcms User Interface
Maui is the Maltcms User Interface, a rich client application for Chromatography-Mass Spectrometry and related research areas. -
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PANDA
A comprehensive and flexible quantification tool for proteomics data
PANDA is a comprehensive and flexib tool for quantitative proteomics data analysis, which is developed based on our solid foundations in quantitative proteomics for years. Several novelties have been implemented in it. First, we implement the advantage algorithms of LFQuant (Proteomics 2012, 12, (23-24), 3475-84) and SILVER (Bioinformatics 2014, 30, (4), 586-7) into PANDA. Second, we consider the state-of-art concept of quantification reliability in this quantitative workflow. On the levels of spectra, peptides and proteins, PANDA works out a few quantitative filters and new scores for quantification confidence. Third, PANDA is designed for processing proteomics big data in parallel. -
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PROMPT is a system for retrieval, analysis, mapping and comparison of proteins. It allows easy mapping of different types of sequence IDs, data retrieval and integration, a multitude of analysis and comparison algorithms and a full-blown easy to use GUI.
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A collection of code, bundled into a single R package, to perform several aspects of data management, image pre-processing, data analysis and statistical inference related to the quantitative analysis of dynamic contrast-enhanced MRI (DCE-MRI).
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An R package for visualising global scale data by easy import & display of country level & gridded data. Rworldmap will also provide access to existing datasets from earth to social sciences and facilitate their combination to provide insights for policy
