research-article

Pareto epsilon-dominance and identifiable solutions for BioCAD modeling

Authors:

Claudio Angione,

Giovanni Carapezza,

Pietro Lió, and

Giuseppe NicosiaAuthors Info & Claims

DAC '13: Proceedings of the 50th Annual Design Automation Conference

May 2013

Article No.: 43, Pages 1 - 9

https://doi.org/10.1145/2463209.2488787

Published: 29 May 2013 Publication History

Abstract

We propose a framework to design metabolic pathways in which many objectives are optimized simultaneously. This allows to characterize the energy signature in models of algal and mitochondrial metabolism. The optimal design and assessment of the model is achieved through a multi-objective optimization technique driven by epsilon-dominance and identifiability analysis. A faster convergence process with robust candidate solutions is permitted by a relaxed Pareto dominance, regulating the granularity of the approximation of the Pareto front. Our framework is also suitable for black-box analysis, enabling to investigate and optimize any biological pathway modeled with ODEs, DAEs, FBA and GPR.

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Digital Library

Cited By

Menchaca-Mendez AMontero EAntonio LZapotecas-Martinez SCoello Coello CRiff M(2019)A Co-Evolutionary Scheme for Multi-Objective Evolutionary Algorithms Based on $\epsilon$ -DominanceIEEE Access10.1109/ACCESS.2019.28969627(18267-18283)Online publication date: 2019
https://doi.org/10.1109/ACCESS.2019.2896962
Patané AConca PCarapezza GSantoro ACostanza JNicosia G(2016)Metabolic Circuit Design Automation by Multi-objective BioCADMachine Learning, Optimization, and Big Data10.1007/978-3-319-51469-7_3(30-44)Online publication date: 25-Dec-2016
https://doi.org/10.1007/978-3-319-51469-7_3
Patane ASantoro ACostanza JCarapezza GNicosia G(2015)Pareto Optimal Design for Synthetic BiologyIEEE Transactions on Biomedical Circuits and Systems10.1109/TBCAS.2015.24672149:4(555-571)Online publication date: Aug-2015
https://doi.org/10.1109/TBCAS.2015.2467214

Index Terms

Pareto epsilon-dominance and identifiable solutions for BioCAD modeling
1. Applied computing
  1. Arts and humanities
    1. Architecture (buildings)
      1. Computer-aided design
  2. Physical sciences and engineering
    1. Engineering
      1. Computer-aided design
2. Hardware

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cover image ACM Conferences

DAC '13: Proceedings of the 50th Annual Design Automation Conference

May 2013

1285 pages

ISBN:9781450320719

DOI:10.1145/2463209

Copyright © 2013 ACM.

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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EDAC: Electronic Design Automation Consortium
SIGDA: ACM Special Interest Group on Design Automation
IEEE-CEDA

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SIGBED: ACM Special Interest Group on Embedded Systems

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Association for Computing Machinery

New York, NY, United States

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Published: 29 May 2013

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DAC '13: The 50th Annual Design Automation Conference 2013

May 29 - June 7, 2013

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Overall Acceptance Rate 1,770 of 5,499 submissions, 32%

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Cited By

Menchaca-Mendez AMontero EAntonio LZapotecas-Martinez SCoello Coello CRiff M(2019)A Co-Evolutionary Scheme for Multi-Objective Evolutionary Algorithms Based on $\epsilon$ -DominanceIEEE Access10.1109/ACCESS.2019.28969627(18267-18283)Online publication date: 2019
https://doi.org/10.1109/ACCESS.2019.2896962
Patané AConca PCarapezza GSantoro ACostanza JNicosia G(2016)Metabolic Circuit Design Automation by Multi-objective BioCADMachine Learning, Optimization, and Big Data10.1007/978-3-319-51469-7_3(30-44)Online publication date: 25-Dec-2016
https://doi.org/10.1007/978-3-319-51469-7_3
Patane ASantoro ACostanza JCarapezza GNicosia G(2015)Pareto Optimal Design for Synthetic BiologyIEEE Transactions on Biomedical Circuits and Systems10.1109/TBCAS.2015.24672149:4(555-571)Online publication date: Aug-2015
https://doi.org/10.1109/TBCAS.2015.2467214

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