Search Results for "seismic data processing software"

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...

dataMAPPs allows routine and efficient processing of data from immunogenicity studies applying the MAPPs peptidomics technology to detect potential MHCI- or MHC-II epitopes as presented by dendritic cells (DC). It features quality control of the raw data, across-sample/across-donor normalization and visualization of results in a heatmap style (heatMAPPs). dataMAPPs' core is a generic R library that can be tailored to specific projects via dedicated control scripts which also allow reproducible recalculation of results. ...

KMWin (Kaplan-Meier for Windows) is a convenient tool for graphical presentation of results from Kaplan-Meier survival time analysis. The programme is based on the statistical software environment R and provides an easy to use graphical interface. As an introduction, see http://dx.plos.org/10.1371/journal.pone.0038960#s2.

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. This website contains the IQuant software, an example data labeled by iTRAQ-8plex for testing and a user's manual. ...

SimAssem is a tool for investigating the performances of species richness estimators across widely ranging assemblages and survey designs. Assemblages are simulated by specifying the: 1) number of species, 2) total abundance of individuals, 3) abundance distribution, 4) spatial configuration, 5) species detection probabilities, 6) survey design, and 7) number of grid cells to survey (out of a square grid comprised of 10,000 cells). SimAssem also processes existing encounter data and formats...

Quick reference for switching between mathematical computation environments for computer algebra, numeric processing and data visualisation. Examples are Matlab, IDL, SPlus, and their open-source counterparts Octave, Scilab, Python+NumPy and R.