MNDIS-NNSYSYOCAOJun 28, 2018

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

arXiv:1807.000382 citationsh-index: 48
AI Analysis

For researchers in control theory and network science, this issue consolidates progress on common challenges in biological networks, with potential cross-domain applicability.

This special issue presents a collection of papers advancing methods for observing, identifying, and controlling biological and biologically inspired networks, addressing challenges like high dimensionality and nonlinearity.

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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