Here, we introduce a “simple to use” yet efficient and panoptic software to addresses shotgun proteomic data analysis termed PatternLab that was initialy published in BMC Bioinformatics in 2008. PatternLab has continued to evolve; an updated manuscript is found in Current Protocols in Bioinformatics.

Here are a few of the PatternLab most used modules:

* The ACFold and TFold methods points differentialy expressed proteins in LC-MS experiments

*The Gene Ontology Explorer (GOEx) aids in the biological interpretation of shotgun proteomic data. Besides its nifty GUI, it stands out for providing data such as the global protein fold changes for the GO groups.

* The Charge Prediction Machine (CPM) predicts the charge states of precursor ions of low resolution ETD MS2 spectra and to enable confident protein identification with low resolution equipment.

* YADA can deisotope and decharge highly charged peptides and assign monoisotopic precursor masses to MS2's turning it suitable especialy for middle down proteomics.