Search Results for "quantitative"

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. ...

TXM is a free and open-source cross-platform Unicode & XML based text analysis environment and graphical client, supporting Windows, Linux and Mac OS X. It can also be used online as a J2EE standard compliant web portal (GWT based) with access control built in. DOWNLOAD LATEST VERSION OF TXM : http://textometrie.ens-lyon.fr/spip.php?rubrique61&lang=en TXM offers a comprehensive range of analysis tools (concordances, collocate search, frequency lists, etc.) based on the powerfull CQP...

...This software is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY. In case you use the package in your work, we do appreciate a citation to a DSS publication. Citation: Yadav et al. (2014), Quantitative scoring of differential drug sensitivity for individually optimized anticancer therapies. Scientific Reports 4, 5193; DOI:10.1038/srep05193 Please visit the link below for details

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).

IQuant is an automated pipeline for quantitative proteomics based upon isobaric tags. It integrates post-processing tool of protein identification and advanced statistical algorithms to process the MS/MS signals generated from the peptides labeled by isobaric tags for quantification. IQuant can run from a graphical user interface (GUI) as well as a command-line interface and work with both Windows and Linux system.

Image analysis software for quantification of cell density in microbial cultures (e.g. S. cerevisiae) growing on solid agar plates. Specialises in detection of extremely low cell densities. Forms part of the Quantitative Fitness Analysis (QFA) workflow: http://research.ncl.ac.uk/qfa/ Suitable for high-throughput, genome-wide analysis of culture libraries when combined with the following qfa R package: http://qfa.r-forge.r-project.org/ This is the version presented, used and demonstrated in the following manuscripts: Lawless et al. 2010 http://dx.doi.org/10.1186/1471-2105-11-287 Addinall et al. 2011 http://dx.doi.org/10.1371/journal.pgen.1001362 Chang et al. 2011 http://dx.doi.org/10.1534/g3.111.000216 Banks et al. 2012 http://dx.doi.org/10.3791/4018 Development has been moved to github, where Colonyzer has undergone several recent improvements, particuarly making installation easier and analysis faster: https://github.com/CnrLwlss/Colonyzer

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

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".

The R package to be built aims at implementing what I did in a few scripts for the preparation of the papers I published in CaGEO and TGIS (see below). Basically this is related to the computation of the distribution of k co-occurrences of spatial events (generalising the contiguity distributions - 2 co-occurrences at distance 0) to derive spatial clustering statistics (mainly using the Shannon entropy, then called the k-spatial entropy) and methods linked to this: SOOk, SelSOOk (see caGEO...