2014 DistributedInformationProcessin

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Subject Headings: Biological System.

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Abstract

Exploring the similarities and differences between distributed computations in biological and computational systems.

Introduction

Biological systems, ranging from the molecular to the cellular to the organism level, are distributed and in most cases operate without central control. Such systems must solve information processing problems that are often very similar to problems faced by computational systems, including coordinated decision making, 29 leader election, 2 routing and navigation, 52 and more.42

Over the last few years our ability to study and model biological systems has improved dramatically. Using advanced sequencing technologies we can now determine the composition of the genomes of hundreds of organisms. For specific cells and tissues we can query the set of active genes, their expression levels, and how their responses change in different conditions and over time. We can also determine which molecules within cells interact and how such interactions are wired to form the control diagram regulating cellular activity. Using this data we can build models of information processing within and between cells and answer questions regarding the methods biological systems use to achieve their goals that were out of reach even a few years ago. This data can also help us understand what computational problems are being solved by biological systems and how, which in turn can lead to specific algorithms that may also benefit computational systems.

References

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 AuthorvolumeDate ValuetitletypejournaltitleUrldoinoteyear
2014 DistributedInformationProcessinSaket Navlakha
Ziv Bar-Joseph
Distributed Information Processing in Biological and Computational Systems10.1145/26782802014