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Description Participants Agenda (pdf)

NIMBioS Tutorial

Network Modeling

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Topic: Network Modeling

Meeting dates: February 4-6, 2019

Location: NIMBioS at the University of Tennessee, Knoxville

Nina Fefferman , Ecology & Evolutionary Biology, Univ. of Tennessee
Lazaros Gallos, DIMACS, Rutgers Univ.
Gonzalo Suarez, Ecology & Evolutionary Biology, Univ. of Tennessee


This tutorial introduced students and interested faculty to the topic of complex networks. The field has grown tremendously over the last 20 years and network science has found numerous applications to fields such as biology, ecology, social sciences, physical sciences, computer science, technology, and urban planning. The tutorial reviewed in detail the main ideas and methods in network science with emphasis on both conceptual aspects and real-world applications. Hands-on activities helped the audience familiarize themselves with practical ways to potentially incorporate network analysis in their own research. No prior knowledge of networks or programming was required.

The tutorial was appropriate for interested faculty, post-docs, and graduate students of any discipline.

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Evaluation Report

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Live Stream. This Tutorial was streamed live.

Network image. Summary Report. TBA

A goal of NIMBioS is to enhance the cadre of researchers capable of interdisciplinary efforts across mathematics and biology. As part of this goal, NIMBioS is committed to promoting diversity in all its activities. Diversity is considered in all its aspects, social and scientific, including gender, ethnicity, scientific field, career stage, geography and type of home institution. Questions regarding diversity issues should be directed to You can read more about our Diversity Plan on our NIMBioS Policies web page. The NIMBioS building is fully handicapped accessible.

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From 2008 until early 2021, NIMBioS was supported by the National Science Foundation through NSF Award #DBI-1300426, with additional support from The University of Tennessee, Knoxville. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
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