Phylo: A Citizen Science Approach for Improving Multiple Sequence Alignment

BACKGROUND: Comparative genomics, or the study of the relationships of genome structure and function across different species, offers a powerful tool for studying evolution, annotating genomes, and understanding the causes of various genetic disorders. However, aligning multiple sequences of DNA, an essential intermediate step for most types of analyses, is a difficult computational task. In parallel, citizen science, an approach that takes advantage of the fact that the human brain is exquisitely tuned to solving specific types of problems, is becoming increasingly popular. There, instances of hard computational problems are dispatched to a crowd of non-expert human game players and solutions are sent back to a central server. METHODOLOGY/PRINCIPAL FINDINGS: We introduce Phylo, a human-based computing framework applying "crowd sourcing" techniques to solve the Multiple Sequence Alignment (MSA) problem. The key idea of Phylo is to convert the MSA problem into a casual game that can be played by ordinary web users with a minimal prior knowledge of the biological context. We applied this strategy to improve the alignment of the promoters of disease-related genes from up to 44 vertebrate species. Since the launch in November 2010, we received more than 350,000 solutions submitted from more than 12,000 registered users. Our results show that solutions submitted contributed to improving the accuracy of up to 70% of the alignment blocks considered. CONCLUSIONS/SIGNIFICANCE: We demonstrate that, combined with classical algorithms, crowd computing techniques can be successfully used to help improving the accuracy of MSA. More importantly, we show that an NP-hard computational problem can be embedded in casual game that can be easily played by people without significant scientific training. This suggests that citizen science approaches can be used to exploit the billions of "human-brain peta-flops" of computation that are spent every day playing games. Phylo is available at: http://phylo.cs.mcgill.ca

Crowd computing as a cooperation problem: an evolutionary approach

Cooperation is one of the socio-economic issues that has received more attention from the physics community. The problem has been mostly considered by studying games such as the Prisoner's Dilemma or the Public Goods Game. Here, we take a step forward by studying cooperation in the context of crowd computing. We introduce a model loosely based on Principal-agent theory in which people (workers) contribute to the solution of a distributed problem by computing answers and reporting to the problem proposer (master). To go beyond classical approaches involving the concept of Nash equilibrium, we work on an evolutionary framework in which both the master and the workers update their behavior through reinforcement learning. Using a Markov chain approach, we show theoretically that under certain----not very restrictive-conditions, the master can ensure the reliability of the answer resulting of the process. Then, we study the model by numerical simulations, finding that convergence, meaning that the system reaches a point in which it always produces reliable answers, may in general be much faster than the upper bounds given by the theoretical calculation. We also discuss the effects of the master's level of tolerance to defectors, about which the theory does not provide information. The discussion shows that the system works even with very large tolerances. We conclude with a discussion of our results and possible directions to carry this research further.This work is supported by the Cyprus Research Promotion Foundation grant TE/HPO/0609(BE)/05, the National Science Foundation (CCF-0937829, CCF-1114930), Comunidad de Madrid grant S2009TIC-1692 and MODELICO-CM, Spanish MOSAICO, PRODIEVO and RESINEE grants and MICINN grant TEC2011-29688-C02-01, and National Natural Science Foundation of China grant 61020106002.Publicad

A Jini-based Prototype Metacomputing Framework

. This paper investigates the possible use of Jini technology for building Java-based metacomputing environments. The paper presents the structure of a prototype Jini metacomputing system. The overall working mechanism and some details of the implementation are described. It is shown that Jini is a suitable technology that deserves the interest of the metacomputing research community.

Trustless grid computing in ConCert

Abstract. We believe that fundamental to the establishment of a grid computing framework where all (not just large organizations) are able to effectively tap into the resources available on the global network is the establishment of trust between grid application developers and resource donors. Resource donors must be able to trust that their security, safety, and privacy policies will be respected by programs that use their systems. In this paper, we present a novel solution based on the notion of certified code that upholds safety, security, and privacy policies by examining intrinsic properties of code. Certified code complements authentication and provides a foundation for a safe, secure, and efficient framework that executes native code. We describe the implementation of such a framework known as the ConCert software. 1 Introduction In recent years, numerous organizations have been vying for donated resources for their grid applications. Potential resource donors are inundated with worthwhile grid projects such as discovering a cure for AIDS, finding large prime numbers, and searching for extraterrestrial intelligence. Part of the difficulty in obtaining resources is establishing trust between the grid application developer and the resource donors. Because resource donors often receive little or no direct reward for their contributions, they demand assurances of safety, security, and privacy to protect themselves from malicious as well as simply unreliable software. In an ideal grid framework, as proposed in Legion [18], users are provided the abstraction of a single virtual machine that automatically distributes work and gathers results. In such a framework, this issue is even more salient because the exchange of code happens automatically