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Protein Models Comparator: Scalable Bioinformatics Computing on the Google App Engine Platform

Published 21 Feb 2011 in cs.CE, cs.DC, and q-bio.BM | (1102.4293v2)

Abstract: The comparison of computer generated protein structural models is an important element of protein structure prediction. It has many uses including model quality evaluation, selection of the final models from a large set of candidates or optimisation of parameters of energy functions used in template-free modelling and refinement. Although many protein comparison methods are available online on numerous web servers, they are not well suited for large scale model comparison: (1) they operate with methods designed to compare actual proteins, not the models of the same protein, (2) majority of them offer only a single pairwise structural comparison and are unable to scale up to a required order of thousands of comparisons. To bridge the gap between the protein and model structure comparison we have developed the Protein Models Comparator (pm-cmp). To be able to deliver the scalability on demand and handle large comparison experiments the pm-cmp was implemented "in the cloud". Protein Models Comparator is a scalable web application for a fast distributed comparison of protein models with RMSD, GDT TS, TM-score and Q-score measures. It runs on the Google App Engine (GAE) cloud platform and is a showcase of how the emerging PaaS (Platform as a Service) technology could be used to simplify the development of scalable bioinformatics services. The functionality of pm-cmp is accessible through API which allows a full automation of the experiment submission and results retrieval. Protein Models Comparator is free software released on the Affero GNU Public Licence and is available with its source code at: http://www.infobiotics.org/pm-cmp This article presents a new web application addressing the need for a large-scale model-specific protein structure comparison and provides an insight into the GAE (Google App Engine) platform and its usefulness in scientific computing.

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