BackgroundBioHackathon 2010 was the third in a series of meetings hosted by the Database Center for Life Sciences (DBCLS) in Tokyo, Japan. The overall goal of the BioHackathon series is to improve the quality and accessibility of life science research data on the Web by bringing together representatives from public databases, analytical tool providers, and cyber-infrastructure researchers to jointly tackle important challenges in the area of in silico biological research.ResultsThe theme of BioHackathon 2010 was the 'Semantic Web', and all attendees gathered with the shared goal of producing Semantic Web data from their respective resources, and/or consuming or interacting those data using their tools and interfaces. We discussed on topics including guidelines for designing semantic data and interoperability of resources. We consequently developed tools and clients for analysis and visualization.ConclusionWe provide a meeting report from BioHackathon 2010, in which we describe the discussions, decisions, and breakthroughs made as we moved towards compliance with Semantic Web technologies - from source provider, through middleware, to the end-consumer.
We focus on the asymmetry of the interaction in the optimal velocity (OV) model, which is a model of self-driven particles, and analytically investigate the effects of the asymmetry on the fluctuation-response relation, which is one of the remarkable relationships in statistical physics. By linearizing a modified OV model, i.e., the backward-looking optimal velocity model, which can easily control the magnitude of asymmetry in the interaction, we derive n coupled linear oscillators with asymmetric interactions. We analytically solve the equations of the n coupled linear oscillators and calculate the response and correlation functions. We find that the fluctuation response relation does not hold in the n coupled linear oscillators with asymmetric interactions. Moreover, as the magnitude of the asymmetry increases, the difference between the response and correlation functions increases .
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.