Hierarchical coordinate systems for understanding complexity and its evolution with applications to genetic regulatory networks

Original article can be found at : http://www.mitpressjournals.org/ Copyright MIT PressBeyond complexity measures, sometimes it is worth in addition investigating how complexity changes structurally, especially in artificial systems where we have complete knowledge about the evolutionary process. Hierarchical decomposition is a useful way of assessing structural complexity changes of organisms modeled as automata, and we show how recently developed computational tools can be used for this purpose, by computing holonomy decompositions and holonomy complexity. To gain insight into the evolution of complexity, we investigate the smoothness of the landscape structure of complexity under minimal transitions. As a proof of concept, we illustrate how the hierarchical complexity analysis reveals symmetries and irreversible structure in biological networks by applying the methods to the lac operon mechanism in the genetic regulatory network of Escherichia coli.Peer reviewe

The Algebraic View of Computation

We argue that computation is an abstract algebraic concept, and a computer is a result of a morphism (a structure preserving map) from a finite universal semigroup.Comment: 13 pages, final version will be published elsewher

Symmetry structure in discrete models of biochemical systems : natural subsystems and the weak control hierarchy in a new model of computation driven by interactions

© 2015 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.Interaction Computing (IC) is inspired by the observation that cell metabolic/regulatory systems construct order dynamically, through constrained interactions between their components and based on a wide range of possible inputs and environmental conditions. The goals of this work are (1) to identify and understand mathematically the natural subsystems and hierarchical relations in natural systems enabling this, and (2) to use the resulting insights to define a new model of computation based on interactions that is useful for both biology and computation. The dynamical characteristics of the cellular pathways studied in Systems Biology relate, mathematically, to the computational characteristics of automata derived from them, and their internal symmetry structures to computational power. Finite discrete automata models of biological systems such as the lac operon, Krebs cycle, and p53-mdm2 genetic regulation constructed from Systems Biology models have canonically associated algebraic structures { transformation semigroups. These contain permutation groups (local substructures exhibiting symmetry) that correspond to "pools of reversibility". These natural subsystems are related to one another in a hierarchical manner by the notion of "weak control ". We present natural subsystems arising from several biological examples and their weak control hierarchies in detail. Finite simple non-abelian groups (SNAGs) are found in biological examples and can be harnessed to realize nitary universal computation. This allows ensembles of cells to achieve any desired finitary computational transformation, depending on external inputs, via suitably constrained interactions. Based on this, interaction machines that grow and change their structure recursively are introduced and applied, providing a natural model of computation driven by interactions.Peer reviewe

Policy Networks: Empirical Evidence and Theoretical Considerations

Political governance in modern societies can no longer be conceived in terms of external government control of society but emerges from a plurality of governing agents. In contemporary policy making, governmental and non-governmental actors are interconnected in complex networks of interaction, exchanging information and other resources. This reader presents the results of empirical network studies in a variety of policy sectors and in different countries. It also provides insights into innovative quantitative and qualitative approaches to network analysis.Part One • Theoretical Considerations 1 Introduction: Studying Policy Networks Bernd Marin and Renate Mayntz 2 Policy Networks and Policy Analysis: Scrutinizing a New Analytical Toolbox Patrick Kenis and Volker Schneider Part Two • Policy Networks in National Policy Domains 3 Organizations in Political Action: Representing Interests in National Policy Making Edward O. Laumann and John P. Heinz with Robert Nelson and Robert Salisbury 4 Policy Networks in the German Telecommunications Domain Volker Schneider and Raymund Werle 5 Policy Networks and Change: The Case of High-Tc Superconductors Dorothea Jansen Part Three • Cross-National Variations in Policy Networks 6 Political Exchange in the German and American Labor Policy Domain Franz Urban Pappi and David Knoke 7 Fencing Off: Central Banks and Networks in Canada and the United States William D. Coleman 8 Policy Networks, Opportunity Structures and Neo-Conservative Reform Strategies in Health Policy Marian Döhler 9 The Preconditions for Policy Networks: Some Findings from a Three-Country Study on Industrial Restructuring Patrick Kenis Contributor