Estimating Information Exchange Performance of Engineered Cell-to-cell Molecular Communications: A Computational Approach

Colton Harper, Massimiliano Pierobon, Maurizio Mazarini

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Biological cells naturally exchange information for adapting to the environment, or even influencing other cells. One of the latest frontiers of synthetic biology stands in engineering cells to harness these natural communication processes for tissue engineering and cancer treatment, amongst others. Although experimental success has been achieved in this direction, approaches to characterize these systems in terms of communication performance and their dependence on design parameters are currently limited. In contrast to more classical communication systems, information in biological cells is propagated through molecules and biochemical reactions, which in general result in nonlinear input-output behaviors with system-evolution-dependent stochastic effects that are not amenable to analytical closed-form characterization. In this paper, a computational approach is proposed to characterize the information exchange in these systems, based on stochastic simulation of biochemical reactions and the estimation of information-theoretic parameters from sample distributions. In particular, this approach focuses on engineered cell-to-cell communications with a single transmitter and receiver, and it is applied to characterize the performance of a realistic system. Numerical results confirm the feasibility of this approach to be at the basis of future forward engineering practices for these communication systems.

Original languageEnglish (US)
Title of host publicationINFOCOM 2018 - IEEE Conference on Computer Communications
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages729-737
Number of pages9
ISBN (Electronic)9781538641286
DOIs
StatePublished - Oct 8 2018
Event2018 IEEE Conference on Computer Communications, INFOCOM 2018 - Honolulu, United States
Duration: Apr 15 2018Apr 19 2018

Publication series

NameProceedings - IEEE INFOCOM
Volume2018-April
ISSN (Print)0743-166X

Other

Other2018 IEEE Conference on Computer Communications, INFOCOM 2018
CountryUnited States
CityHonolulu
Period4/15/184/19/18

Fingerprint

Communication
Communication systems
Cell engineering
Oncology
Tissue engineering
Transmitters
Molecules
Synthetic Biology

Keywords

  • Molecular Communication
  • Mutual Information
  • Stochastic Simulation
  • Synthetic Biology

ASJC Scopus subject areas

  • Computer Science(all)
  • Electrical and Electronic Engineering

Cite this

Harper, C., Pierobon, M., & Mazarini, M. (2018). Estimating Information Exchange Performance of Engineered Cell-to-cell Molecular Communications: A Computational Approach. In INFOCOM 2018 - IEEE Conference on Computer Communications (pp. 729-737). [8485834] (Proceedings - IEEE INFOCOM; Vol. 2018-April). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/INFOCOM.2018.8485834

Estimating Information Exchange Performance of Engineered Cell-to-cell Molecular Communications : A Computational Approach. / Harper, Colton; Pierobon, Massimiliano; Mazarini, Maurizio.

INFOCOM 2018 - IEEE Conference on Computer Communications. Institute of Electrical and Electronics Engineers Inc., 2018. p. 729-737 8485834 (Proceedings - IEEE INFOCOM; Vol. 2018-April).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Harper, C, Pierobon, M & Mazarini, M 2018, Estimating Information Exchange Performance of Engineered Cell-to-cell Molecular Communications: A Computational Approach. in INFOCOM 2018 - IEEE Conference on Computer Communications., 8485834, Proceedings - IEEE INFOCOM, vol. 2018-April, Institute of Electrical and Electronics Engineers Inc., pp. 729-737, 2018 IEEE Conference on Computer Communications, INFOCOM 2018, Honolulu, United States, 4/15/18. https://doi.org/10.1109/INFOCOM.2018.8485834
Harper C, Pierobon M, Mazarini M. Estimating Information Exchange Performance of Engineered Cell-to-cell Molecular Communications: A Computational Approach. In INFOCOM 2018 - IEEE Conference on Computer Communications. Institute of Electrical and Electronics Engineers Inc. 2018. p. 729-737. 8485834. (Proceedings - IEEE INFOCOM). https://doi.org/10.1109/INFOCOM.2018.8485834
Harper, Colton ; Pierobon, Massimiliano ; Mazarini, Maurizio. / Estimating Information Exchange Performance of Engineered Cell-to-cell Molecular Communications : A Computational Approach. INFOCOM 2018 - IEEE Conference on Computer Communications. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 729-737 (Proceedings - IEEE INFOCOM).
@inproceedings{9b51e5eade494d22a81f1890206f68bb,
title = "Estimating Information Exchange Performance of Engineered Cell-to-cell Molecular Communications: A Computational Approach",
abstract = "Biological cells naturally exchange information for adapting to the environment, or even influencing other cells. One of the latest frontiers of synthetic biology stands in engineering cells to harness these natural communication processes for tissue engineering and cancer treatment, amongst others. Although experimental success has been achieved in this direction, approaches to characterize these systems in terms of communication performance and their dependence on design parameters are currently limited. In contrast to more classical communication systems, information in biological cells is propagated through molecules and biochemical reactions, which in general result in nonlinear input-output behaviors with system-evolution-dependent stochastic effects that are not amenable to analytical closed-form characterization. In this paper, a computational approach is proposed to characterize the information exchange in these systems, based on stochastic simulation of biochemical reactions and the estimation of information-theoretic parameters from sample distributions. In particular, this approach focuses on engineered cell-to-cell communications with a single transmitter and receiver, and it is applied to characterize the performance of a realistic system. Numerical results confirm the feasibility of this approach to be at the basis of future forward engineering practices for these communication systems.",
keywords = "Molecular Communication, Mutual Information, Stochastic Simulation, Synthetic Biology",
author = "Colton Harper and Massimiliano Pierobon and Maurizio Mazarini",
year = "2018",
month = "10",
day = "8",
doi = "10.1109/INFOCOM.2018.8485834",
language = "English (US)",
series = "Proceedings - IEEE INFOCOM",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "729--737",
booktitle = "INFOCOM 2018 - IEEE Conference on Computer Communications",

}

TY - GEN

T1 - Estimating Information Exchange Performance of Engineered Cell-to-cell Molecular Communications

T2 - A Computational Approach

AU - Harper, Colton

AU - Pierobon, Massimiliano

AU - Mazarini, Maurizio

PY - 2018/10/8

Y1 - 2018/10/8

N2 - Biological cells naturally exchange information for adapting to the environment, or even influencing other cells. One of the latest frontiers of synthetic biology stands in engineering cells to harness these natural communication processes for tissue engineering and cancer treatment, amongst others. Although experimental success has been achieved in this direction, approaches to characterize these systems in terms of communication performance and their dependence on design parameters are currently limited. In contrast to more classical communication systems, information in biological cells is propagated through molecules and biochemical reactions, which in general result in nonlinear input-output behaviors with system-evolution-dependent stochastic effects that are not amenable to analytical closed-form characterization. In this paper, a computational approach is proposed to characterize the information exchange in these systems, based on stochastic simulation of biochemical reactions and the estimation of information-theoretic parameters from sample distributions. In particular, this approach focuses on engineered cell-to-cell communications with a single transmitter and receiver, and it is applied to characterize the performance of a realistic system. Numerical results confirm the feasibility of this approach to be at the basis of future forward engineering practices for these communication systems.

AB - Biological cells naturally exchange information for adapting to the environment, or even influencing other cells. One of the latest frontiers of synthetic biology stands in engineering cells to harness these natural communication processes for tissue engineering and cancer treatment, amongst others. Although experimental success has been achieved in this direction, approaches to characterize these systems in terms of communication performance and their dependence on design parameters are currently limited. In contrast to more classical communication systems, information in biological cells is propagated through molecules and biochemical reactions, which in general result in nonlinear input-output behaviors with system-evolution-dependent stochastic effects that are not amenable to analytical closed-form characterization. In this paper, a computational approach is proposed to characterize the information exchange in these systems, based on stochastic simulation of biochemical reactions and the estimation of information-theoretic parameters from sample distributions. In particular, this approach focuses on engineered cell-to-cell communications with a single transmitter and receiver, and it is applied to characterize the performance of a realistic system. Numerical results confirm the feasibility of this approach to be at the basis of future forward engineering practices for these communication systems.

KW - Molecular Communication

KW - Mutual Information

KW - Stochastic Simulation

KW - Synthetic Biology

UR - http://www.scopus.com/inward/record.url?scp=85055779173&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85055779173&partnerID=8YFLogxK

U2 - 10.1109/INFOCOM.2018.8485834

DO - 10.1109/INFOCOM.2018.8485834

M3 - Conference contribution

AN - SCOPUS:85055779173

T3 - Proceedings - IEEE INFOCOM

SP - 729

EP - 737

BT - INFOCOM 2018 - IEEE Conference on Computer Communications

PB - Institute of Electrical and Electronics Engineers Inc.

ER -