CNetS team studies generalized modularity in complex networks & Systems

mediumModularity in complex systems can be observed in networks and across dynamical states, time scales, and in response to different kinds of perturbations. In a paper published in Physical Review E (Rapid Communication), Kolchinsky, Gates & Rocha propose a principled alternative to detecting communities in static and dynamical networks. The method demonstrates that standard modularity measures on static networks can be seen as a special case of measuring the spread of perturbations in dynamical systems. Thus, the new method offers a powerful tool for exploring the modular organization of complex dynamical systems.… continue reading.

Awards at CCS 2015

Optimized-IU_poster_5_botsThe CNetS poster “The Rise of Social Bots in Online Social Networks” by Emilio Ferrara, Onur Varol, Prashant Shiralkar, Clayton Davis, Filippo Menczer, and Alessandro Flammini won a Best Poster Award at CCS 2015. The poster was presented by Clayton Davis. The results will also appear in the paper “The Rise of Social Bots” to be published in Comm. ACM (in press, preprint).

The paper “Modularity and the Spread of Perturbations in Complex Dynamical Systems” by Artemy Kolchinsky, Alexander J. Gates and Luis M. Rocha, and the poster “Information Theoretic Structures of the French Revolution” by Alexander Barron, Simon DeDeo and Rebecca Spang won additional awards.

Finally, our former postdoctoral scientist Bruno Gonçalves (now tenured faculty member at Aix-Marseille Université) received a Junior Scientist Award from the Complex Systems Society for his contributions to the study of human social behavior from large-scale online attention and behavioral data. This is the second Junior Scientist Award for CNetS (the first was won by Filippo Radicchi).

Congratulations to the CNetS team!

  … continue reading.

New CASCI papers on Complex Networks

Read new papers from CASCI on developing the mathematical toolbox available to deal with computing distances on weighted graphs, applying distance closures for computational fact checking, and computing multi-scale integration in brain networks:

T. Simas and L.M. Rocha [2015].”Distance Closures on Complex Networks”. Network Science, doi:10.1017/nws.2015.11.

G.L. Ciampaglia, P. Shiralkar, L.M. Rocha, J. Bollen, F. Menczer, A. Flammini [2015]. “Computational fact checking from knowledge networks.” PLoS One. In Press. arXiv:1501.03471.

A. Kolchinsky, M. P. Van Den Heuvel, A. Griffa, P. Hagmann, L.M. Rocha, O. Sporns, J. Goni [2014]. “Multi-scale Integration and Predictability in Resting State Brain Activity”. Frontiers in Neuroinformatics, 8:66. doi: 10.3389/fninf.2014.00066. … continue reading.

NIH Project to study Drug-Drug Interaction

Prof. Luis Rocha from CNETS at IU Bloomington, Prof. Lang Li from IUPUI Medical School, and Prof. Hagit Shatkay from the University of Delaware have been awarded a four-year, $1.7M grant from NIH/NLM to study the large-scale extraction of drug-Interaction from medical text. Drug-drug interaction (DDI) leads to adverse drug reactions, emergency room visits and hospitalization, thus posing a major challenge to public health. To circumvent risk to patients, and to expedite biomedical research, both clinicians and biologists must have access to all available knowledge about potential DDI, and understand both causes and consequences of such interactions. However, mere identification of interactions does not directly support such understanding, as evidence for DDI varies broadly, from reports of molecular interactions in basic-science journals, to clinical descriptions of adverse-effects in a myriad of medical publications. This project will develop tools that focus directly on large-scale identification and gathering of various types of reliable experimental evidence of DDI from diverse sources. The successful completion of the project will provide clinicians and biologists with substantiated knowledge about drug interactions and with informatics tools to obtain such information on a large-scale, laying the basis for preventing adverse drug reactions and for exploring alternative treatments. … continue reading.