PROTICdb is a web-based application designed to store and analyze proteome data obtained by mass spectrometry.

The PAPPSO PROTICdb public site is available here

ALL-P is a statistical framework based on a hierarchical modeling that takes into account shared peptide information for estimating protein abundances. ALL-P performs a simultaneous analysis of all the quantified peptides, handling the biological and technical errors as well as the peptide effect. Compared to a method based on the analysis of one protein at a time that does not include shared peptides (ONE-P method), ALL-P proved to be far more reliable for estimating protein abundances and testing abundance changes.

This Java application, stores all your sequence databases in a single folder (repository). It offers :

• conservation of metadata : database origin, species, number of protein, download site, …
• translation of DNA into protein
• creation of decoy protein databases (protein reverse, random, peptide reverse
• combination of different existing databases

This application can managed multiple repository.

The classical method for protein identification of LC-MS/MS data uses database searching and matching, as it is the case in Mascot, Sequest or X!Tandem softwares. However, these identifications are possible only if the protein being searched is present in the database. To address this problem the de novo interpretation strategy can be used instead. There exist softwares that use this strategy, but they are often difficult to use in a direct, automated way.

Description

Metaprotr is an R package that contains a set of tools for descriptive analysis of metaproteomics data generated from high-throughput mass spectrometry instruments. These tools allow to cluster peptides and proteins abundance, expressed as spectral counts, and to manipulate them in groups of metaproteins. This information can be represented using multiple visualization functions to portray the global metaproteome landscape and to differentiate samples or conditions, in terms of abundance of metaproteins, taxonomic levels and/or functional annotation. The provided tools allow to implement flexible analytical pipelines that can be easily applied to studies interested in metaproteomics analysis.