P2P proteomics -- data sharing for enhanced protein identification

This is an open access article distributed under the terms of the Creative Commons Attribution License.Background: In order to tackle the important and challenging problem in proteomics of identifying known and new protein sequences using high-throughput methods, we propose a data-sharing platform that uses fully distributed P2P technologies to share specifications of peer-interaction protocols and service components. By using such a platform, information to be searched is no longer centralised in a few repositories but gathered from experiments in peer proteomics laboratories, which can subsequently be searched by fellow researchers. Methods: The system distributively runs a data-sharing protocol specified in the Lightweight Communication Calculus underlying the system through which researchers interact via message passing. For this, researchers interact with the system through particular components that link to database querying systems based on BLAST and/or OMSSA and GUI-based visualisation environments. We have tested the proposed platform with data drawn from preexisting MS/MS data reservoirs from the 2006 ABRF (Association of Biomolecular Resource Facilities) test sample, which was extensively tested during the ABRF Proteomics Standards Research Group 2006 worldwide survey. In particular we have taken the data available from a subset of proteomics laboratories of Spain's National Institute for Proteomics, ProteoRed, a network for the coordination, integration and development of the Spanish proteomics facilities. Results and Discussion: We performed queries against nine databases including seven ProteoRed proteomics laboratories, the NCBI Swiss-Prot database and the local database of the CSIC/UAB Proteomics Laboratory. A detailed analysis of the results indicated the presence of a protein that was supported by other NCBI matches and highly scored matches in several proteomics labs. The analysis clearly indicated that the protein was a relatively high concentrated contaminant that could be present in the ABRF sample. This fact is evident from the information that could be derived from the proposed P2P proteomics system, however it is not straightforward to arrive to the same conclusion by conventional means as it is difficult to discard organic contamination of samples. The actual presence of this contaminant was only stated after the ABRF study of all the identifications reported by the laboratories.This research has been supported by the OpenKnowledge STREP (FP6-027253) funded by the European Commission; by grants BIO2009-11735, CONSOLIDER-INGENIO 2010 Agreement Technologies (CSD2007-0022) and CBIT (TIN2010-16306) funded by Spain's Ministerio de Ciencia e Innovación; and by the Generalitat de Catalunya (2009-SGR-1434).Peer Reviewe

Models of Interaction as a Grounding for Peer to Peer Knowledge Sharing

Most current attempts to achieve reliable knowledge sharing on a large scale have relied on pre-engineering of content and supply services. This, like traditional knowledge engineering, does not by itself scale to large, open, peer to peer systems because the cost of being precise about the absolute semantics of services and their knowledge rises rapidly as more services participate. We describe how to break out of this deadlock by focusing on semantics related to interaction and using this to avoid dependency on a priori semantic agreement; instead making semantic commitments incrementally at run time. Our method is based on interaction models that are mobile in the sense that they may be transferred to other components, this being a mechanism for service composition and for coalition formation. By shifting the emphasis to interaction (the details of which may be hidden from users) we can obtain knowledge sharing of sufficient quality for sustainable communities of practice without the barrier of complex meta-data provision prior to community formation

FRIENDS NO MORE: OSTRACISM IN MULTI-AGENT SYSTEMS

In a normative society there are two main problems: defining norms and enforcing them. Enforcement becomes a complex issue as societies become more decentralized and open. We propose a distributed mechanism to enforce norms by ostracizing agents that do not abide by them. The simulations have shown that, although complete ostracism is not always possible, the mechanism reduces substantially the number of norm violation victims

A Social-Network Defence against Whitewashing

We provide a defence against whitewashing for trust assessment mechanisms (TAM) by using an underlying social network in MAS and P2P. Since interaction requests are routed through the social network, routers can block requests from portions of the network known for whitewashing. Furthermore, by limiting feedback spread to the interaction routers, the trust assessment can be done without querying for feedback with a small loss in efficiency.Peer Reviewe