Dataset Information

Uncovering space-independent communities in spatial networks.

ABSTRACT: Many complex systems are organized in the form of a network embedded in space. Important examples include the physical Internet infrastructure, road networks, flight connections, brain functional networks, and social networks. The effect of space on network topology has recently come under the spotlight because of the emergence of pervasive technologies based on geolocalization, which constantly fill databases with people's movements and thus reveal their trajectories and spatial behavior. Extracting patterns and regularities from the resulting massive amount of human mobility data requires the development of appropriate tools for uncovering information in spatially embedded networks. In contrast with most works that tend to apply standard network metrics to any type of network, we argue in this paper for a careful treatment of the constraints imposed by space on network topology. In particular, we focus on the problem of community detection and propose a modularity function adapted to spatial networks. We show that it is possible to factor out the effect of space in order to reveal more clearly hidden structural similarities between the nodes. Methods are tested on a large mobile phone network and computer-generated benchmarks where the effect of space has been incorporated.

SUBMITTER: Expert P

PROVIDER: S-EPMC3093492 | biostudies-literature | 2011 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Uncovering space-independent communities in spatial networks.

Expert Paul P Evans Tim S TS Blondel Vincent D VD Lambiotte Renaud R

Proceedings of the National Academy of Sciences of the United States of America 20110425 19

Many complex systems are organized in the form of a network embedded in space. Important examples include the physical Internet infrastructure, road networks, flight connections, brain functional networks, and social networks. The effect of space on network topology has recently come under the spotlight because of the emergence of pervasive technologies based on geolocalization, which constantly fill databases with people's movements and thus reveal their trajectories and spatial behavior. Extra ...[more]

PMID: 21518910

Similar Datasets

Project description:The relative importance of spatial and temporal variability in shaping the distribution of soil microbial communities at a large spatial scale remains poorly understood. Here, we explored the relative importance of space versus time when predicting the distribution of soil bacterial and fungal communities across North China Plain in two contrasting seasons (summer versus winter). Although we found that microbial alpha (number of phylotypes) and beta (changes in community composition) diversities differed significantly between summer and winter, space rather than season explained more of the spatiotemporal variation of soil microbial alpha and beta diversities. Environmental covariates explained some of microbial spatiotemporal variation observed, with fast-changing environmental covariates-climate variables, soil moisture, and available nutrient-likely being the main factors that drove the seasonal variation found in bacterial and fungal beta diversities. Using random forest modeling, we further identified a group of microbial exact sequence variants (ESVs) as indicators of summer and winter seasons and for which relative abundance was associated with fast-changing environmental variables (e.g., soil moisture and dissolved organic nitrogen). Together, our empirical field study's results suggest soil microbial seasonal variation could arise from the changes of fast-changing environmental variables, thus providing integral support to the large emerging body of snapshot studies related to microbial biogeography.IMPORTANCE Both space and time are key factors that regulate microbial community, but microbial temporal variation is often ignored at a large spatial scale. In this study, we compared spatial and seasonal effects on bacterial and fungal diversity variation across an 878-km transect and found direct evidence that space is far more important than season in regulating the soil microbial community. Partitioning the effect of season, space and environmental variables on microbial community, we further found that fast-changing environmental factors contributed to microbial temporal variation.

Dataset Information

Uncovering space-independent communities in spatial networks.

Publications

Uncovering space-independent communities in spatial networks.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets