PatternLab

From Mswiki

PatternLab for proteomics
PatternLab for proteomics is a computational environment that provides existing and new algorithms to analyze spectral counting data. One of the new strategies is the ACFold that combines expression fold changes, the AC test, and a theoretical false-discovery rate estimator. It stands out because it can compare data acquired with different protocols (e.g., a multi-surfactant shotgun approach) or pairwise experiments with one replicate. To help gain biological insight, PatternLab also leverages the gene ontology database in a tool named GOEx that, differently than other tools, adds protein fold changes to the over-representation statistics. PatternLab can also do proportional Venn Diagram. It project page is http://pcarvalho.com/patternlab
Runs on windows >= XP)

Its home page ports a MudPIT simulator that can be install in your computer should you have to explain its principles to one from a different field (Windows >=XP).

Recently, a new software was added to the package:
Charge Prediction Machine (CPM) is a tool to infer charge states in ETD spectra (up to +7). It has roots in the Bayesian decision theory and uses a semi-supervised learning approach. Briefly, this means it can further learn from set to be classified to further improve results. CPM has a GUI, but can also run using the command prompt to be seamlesly integrated into pipelines and remotely executed in the linux servers. Designed for Windows (>=XP), Linux, and Mac.