16 research outputs found
Topological Cluster Analysis Reveals the Systemic Organization of the Caenorhabditis elegans Connectome
The modular organization of networks of individual neurons interwoven through synapses has not been fully explored due to the incredible complexity of the connectivity architecture. Here we use the modularity-based community detection method for directed, weighted networks to examine hierarchically organized modules in the complete wiring diagram (connectome) of Caenorhabditis elegans (C. elegans) and to investigate their topological properties. Incorporating bilateral symmetry of the network as an important cue for proper cluster assignment, we identified anatomical clusters in the C. elegans connectome, including a body-spanning cluster, which correspond to experimentally identified functional circuits. Moreover, the hierarchical organization of the five clusters explains the systemic cooperation (e.g., mechanosensation, chemosensation, and navigation) that occurs among the structurally segregated biological circuits to produce higher-order complex behaviors
Overlapping community detection in complex networks using symmetric binary matrix factorization
Massive multi-agent data-driven simulations of the github ecosystem
Simulating and predicting planetary-scale techno-social systems poses heavy computational and modeling challenges. The DARPA
SocialSim program set the challenge to model the evolution of GitHub, a
large collaborative software-development ecosystem, using massive multiagent simulations. We describe our best performing models and our
agent-based simulation framework, which we are currently extending to
allow simulating other planetary-scale techno-social systems. The challenge problem measured participantâs ability, given 30 months of metadata on user activity on GitHub, to predict the next monthsâ activity
as measured by a broad range of metrics applied to ground truth, using
agent-based simulation. The challenge required scaling to a simulation of
roughly 3 million agents producing a combined 30 million actions, acting
on 6 million repositories with commodity hardware. It was also important to use the data optimally to predict the agentâs next moves. We
describe the agent framework and the data analysis employed by one of
the winning teams in the challenge. Six different agent models were tested
based on a variety of machine learning and statistical methods. While
no single method proved the most accurate on every metric, the broadly
most successful sampled from a stationary probability distribution of
actions and repositories for each agent. Two reasons for the success of
these agents were their use of a distinct characterization of each agent,
and that GitHub users change their behavior relatively slowl
Design of magnetically levitated rotors in a large flywheel energy storage system from a stability standpoint
Optimizing drugâtarget interaction prediction based on random walk on heterogeneous networks
Googling social interactions : web search engine based social network construction
Social network analysis has long been an untiring topic of sociology. However, until the era of information technology, the availability of data, mainly collected by the traditional method of personal survey, was highly limited and prevented large-scale analysis. Recently, the exploding amount of automatically generated data has completely changed the pattern of research. For instance, the enormous amount of data from so-called high-throughput biological experiments has introduced a systematic or network viewpoint to traditional biology. Then, is âhigh-throughputâ sociological data generation possible? Google, which has become one of the most influential symbols of the new Internet paradigm within the last ten years, might provide torrents of data sources for such study in this (now and forthcoming) digital era. We investigate social networks between people by extracting information on the Web and introduce new tools of analysis of such networks in the context of statistical physics of complex systems or socio-physics. As a concrete and illustrative example, the members of the 109th United States Senate are analyzed and it is demonstrated that the methods of construction and analysis are applicable to various other weighted networks