Introduction to the Special Issue on Approaches to Control Biological and Biologically Inspired Networks

Reka Albert; John Baillieul; Adilson E. Motter

doi:10.1109/TCNS.2018.2836303

Introduction to the Special Issue on Approaches to Control Biological and Biologically Inspired Networks

Reka Albert, John Baillieul, Adilson E. Motter

Research output: Contribution to journal › Article › peer-review

3 Scopus citations

Abstract

The emerging field at the intersection of quantitative biology, network modeling, and control theory has enjoyed significant progress in recent years. This Special Issue brings together a selection of papers on complementary approaches to observe, identify, and control biological and biologically inspired networks. These approaches advance the state of the art in the field by addressing challenges common to many such networks, including high dimensionality, strong nonlinearity, uncertainty, and limited opportunities for observation and intervention. Because these challenges are not unique to biological systems, it is expected that many of the results presented in these contributions will also find applications in other domains, including physical, social, and technological networks.

Original language	English (US)
Pages (from-to)	690-693
Number of pages	4
Journal	IEEE Transactions on Control of Network Systems
Volume	5
Issue number	2
DOIs	https://doi.org/10.1109/TCNS.2018.2836303
State	Published - Jun 2018

All Science Journal Classification (ASJC) codes

Control and Systems Engineering
Signal Processing
Computer Networks and Communications
Control and Optimization

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10.1109/TCNS.2018.2836303

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abstract = "The emerging field at the intersection of quantitative biology, network modeling, and control theory has enjoyed significant progress in recent years. This Special Issue brings together a selection of papers on complementary approaches to observe, identify, and control biological and biologically inspired networks. These approaches advance the state of the art in the field by addressing challenges common to many such networks, including high dimensionality, strong nonlinearity, uncertainty, and limited opportunities for observation and intervention. Because these challenges are not unique to biological systems, it is expected that many of the results presented in these contributions will also find applications in other domains, including physical, social, and technological networks.",

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Introduction to the Special Issue on Approaches to Control Biological and Biologically Inspired Networks

Abstract

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