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End-to-end molecular communication channels in cell metabolism: an information theoretic study

Published: 27 September 2017 Publication History

Abstract

The opportunity to control and fine-tune the behavior of biological cells is a fascinating possibility for many diverse disciplines, ranging from medicine and ecology, to chemical industry and space exploration. While synthetic biology is providing novel tools to reprogram cell behavior from their genetic code, many challenges need to be solved before it can become a true engineering discipline, such as reliability, safety assurance, reproducibility and stability. This paper aims to understand the limits in the controllability of the behavior of a natural (non-engineered) biological cell. In particular, the focus is on cell metabolism, and its natural regulation mechanisms, and their ability to react and change according to the chemical characteristics of the external environment. To understand the aforementioned limits of this ability, molecular communication is used to abstract biological cells into a series of channels that propagate information on the chemical composition of the extracellular environment to the cell's behavior in terms of uptake and consumption of chemical compounds, and growth rate. This provides an information-theoretic framework to analyze the upper bound limit to the capacity of these channels to propagate information, which is based on a well-known and computationally efficient metabolic simulation technique. A numerical study is performed on two human gut microbes, where the upper bound is estimated for different environmental compounds, showing there is a potential for future practical applications.

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  1. End-to-end molecular communication channels in cell metabolism: an information theoretic study

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    cover image ACM Other conferences
    NanoCom '17: Proceedings of the 4th ACM International Conference on Nanoscale Computing and Communication
    September 2017
    169 pages
    ISBN:9781450349314
    DOI:10.1145/3109453
    • General Chairs:
    • Alan Davy,
    • John Federici
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    New York, NY, United States

    Publication History

    Published: 27 September 2017

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    Author Tags

    1. cell metabolism
    2. information theory
    3. molecular communication

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    • NIH
    • US NSF

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    NANOCOM '17

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    Overall Acceptance Rate 97 of 135 submissions, 72%

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    View all
    • (2023)Evolutionary generative adversarial network based end-to-end learning for MIMO molecular communication with drift systemNano Communication Networks10.1016/j.nancom.2023.10045637(100456)Online publication date: Sep-2023
    • (2021)A Survey of Molecular Communication in Cell Biology: Establishing a New Hierarchy for Interdisciplinary ApplicationsIEEE Communications Surveys & Tutorials10.1109/COMST.2021.306611723:3(1494-1545)Online publication date: Nov-2022
    • (2021)Charting a New Frontier Integrating Mathematical Modeling in Complex Biological Systems from Molecules to EcosystemsIntegrative and Comparative Biology10.1093/icb/icab16561:6(2255-2266)Online publication date: 20-Jul-2021
    • (2020)A Comprehensive Survey on Hybrid Communication in Context of Molecular Communication and Terahertz Communication for Body-Centric NanonetworksIEEE Transactions on Molecular, Biological and Multi-Scale Communications10.1109/TMBMC.2020.30171466:2(107-133)Online publication date: Nov-2020
    • (2020)Modeling Diffusion and Chemical Reactions to Analyze Redox-Based Molecular-Electrical CommunicationICC 2020 - 2020 IEEE International Conference on Communications (ICC)10.1109/ICC40277.2020.9148750(1-7)Online publication date: Jun-2020
    • (2019)Microbiome-Gut-Brain Axis as a Biomolecular Communication Network for the Internet of Bio-NanoThingsIEEE Access10.1109/ACCESS.2019.29423127(136161-136175)Online publication date: 2019
    • (2018)Applying molecular communication theory to estimate information loss in cell signal transductionProceedings of the 5th ACM International Conference on Nanoscale Computing and Communication10.1145/3233188.3233202(1-7)Online publication date: 5-Sep-2018
    • (2018)Thermodynamic Properties of Molecular Communication2018 IEEE International Symposium on Information Theory (ISIT)10.1109/ISIT.2018.8437793(2545-2549)Online publication date: Jun-2018

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