University of Alberta
Department of Computer Science
Proteome Analyst
Proteome Analyst (PA) is a publicly-available, high-throughput, Web-based system for predicting various properties of each protein in an entire proteome. Using machine-learned classifiers, PA can predict, for example, the GeneQuiz general function and Gene Ontology (GO) molecular function of a protein. In addition, PA is currently the most-accurate and most-comprehensive system for predicting subcellular localization, the location within a cell where a protein performs its main function. Two other capabilities of PA are notable. First, PA can create a custom classifier to predict a new property, without requiring any programming, based on labeled training data (i.e., a set of examples, each with the correct classification label), provided by a user. PA has been used to create custom classifiers for potassium-ion channel proteins and other general-function ontologies. Second, PA provides a sophisticated explanation feature that shows why one prediction is chosen over another. The PA system produces a Naïve Bayes classifier, which is amenable to a graphical and interactive approach to explanations for its predictions; transparent predictions increase the user’s confidence in, and understanding of, PA.
Wishart Research Group
Proteome Analyst is currently maintained by the Wishart Research Group. The Wishart Research Group has many projects on the go, and Proteome Analyst is but one of them. Visit the site and check out what's going on in the Wishart Research Group
News
January 1st, 2014
Proteome Analyst 3

Proeome Analyst 3.0 (PA3) has been released. PA3 features a new user interface, and Support Vector Machine classifiers. PA3's classifiers have been trained using data from SwissProt 49.

Please check out the latest iteration of the Proteome Analyst 3.0 system.

You can sign up for a free user account (highly recommanded) or try out PA3 with the guest login and pass "pa3guest" (please be aware that data uploaded to the guest account will be public and guest data will be deleted on a rountine basis).

Copyright © 2004
Bioinformatics Research Group
University of Alberta
Contact Us