In his celebrated book "What is Life?" Schrodinger proposed using the properties of living systems to constrain unknown features of life. Here we propose an inverse approach and suggest using biology as a means to constrain unknown physics. We focus on information and causation, as their widespread use in biology is the most problematic aspect of life from the perspective of fundamental physics. Our proposal is cast as a methodology for identifying potentially distinctive features of the informational architecture of biological systems, as compared to other classes of physical system. To illustrate our approach, we use as a case study a Boolean network model for  the cell cycle regulation of the single-celled fission yeast (Schizosaccharomyces Pombe) and compare its informational properties to two classes of null model that share commonalities in their causal structure . We report patterns in local information processing and storage that do indeed distinguish biological from random  . Conversely, we find that integrated information, which serves as a  measure of "emergent" information processing, does not differ from random for the case presented. We discuss implications for our understanding of the informational architecture of the fission yeast cell cycle network and for illuminating any distinctive physics  operative in life.
We compare the informational architecture of biological and random networks to identify informational features that may distinguish biological networks from random. The study presented here focuses on the Boolean network model for regulation of the cell cycle of the fission yeast Schizosaccharomyces Pombe. We compare calculated values of local and global information measures for the fission yeast cell cycle to the same measures as applied to two different classes of random networks: random and scale-free . We report patterns in local information processing and storage that do indeed distinguish biological from random , associated with control nodes that regulate the function of the fission yeast cell cycle network . Conversely, we find that integrated information, which serves as a global measure of "emergent" information processing, does not differ from random for the case presented. We discuss implications for our understanding of the informational architecture of the fission yeast cell cycle network in particular, and more generally for illuminating any distinctive physics that may be operative in life.
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In his celebrated book "What is Life?" Schrodinger proposed using the properties of living systems to constrain unknown features of life. Here we propose an inverse approach and suggest using biology as a means to constrain unknown physics. We focus on information and causation, as their widespread use in biology is the most problematic aspect of life from the perspective of fundamental physics. Our proposal is cast as a methodology for identifying potentially distinctive features of the
We compare the
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systems, as compared to other classes of physical system. To illustrate our approach, we use as a case study a
and random networks to identify informational features that may distinguish biological networks from random. The study presented here focuses on the
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regulation of
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regulation of the single-celled fission yeast (Schizosaccharomyces Pombe) and compare its informational properties to two classes
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null model that share commonalities in their causal structure
the fission yeast Schizosaccharomyces Pombe. We compare calculated values of local and global information measures for the fission yeast cell cycle to the same measures as applied to two different classes of random networks: random and scale-free
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, associated with control nodes that regulate the function of the fission yeast cell cycle network
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global
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and
in particular, and more generally
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that may be