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An algorithm for initial fluxes of metabolic P systems

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TLDR
Here a heuristic algorithm for estimating the initial fluxes of biological reactions by starting from experimental data is proposed, that is tested in two case studies.
Abstract
A central issue in systems biology is the study of efficient methods inferring fluxes of biological reactions by starting from experimental data. Among the different techniques proposed in the last years, the theory of Metabolic P systems, which is based on the Log-Gain principle, proved to be helpful for deducing biologi- cal fluxes from temporal series of observed dynamics. According to this approach, the algebraic systems provided by the Log-Gain principle determine the reaction fluxes underlying a system dynamics when initial fluxes are known. Here we propose a heuristic algorithm for estimating the initial fluxes, that is tested in two case studies.

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Citations
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Journal ArticleDOI

Data analysis pipeline from laboratory to MP models

TL;DR: A workflow for data analysis is introduced to synthesize flux regulation maps of a Metabolic P system from time series of data observed in laboratory, and interesting experimental results came out in the context of their residual analysis for model validation.
Book ChapterDOI

From p to MP systems

TL;DR: A synthetic algebraic formulation of MP system is given, and the log-gain theory of MP systems is outlined, by discussing the research perspectives and the methodological aspects of this approach.
Proceedings ArticleDOI

Metabolic Computing

TL;DR: This paper thinks that this metabolic computing model has both high fault tolerance and sustainability, and proposes two new algorithms, namely bubbling and drifting, which are proposed in this paper.
Book ChapterDOI

Regulation and covering problems in MP systems

TL;DR: Some initial results are reported regarding the efficient computation of regulation fluxes in metabolic P systems by means of Log-gain theory, which shows that the system dynamics can be linearized, in such a way to be described by a recurrence equations system.
References
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Book

Optimization by Vector Space Methods

TL;DR: This book shows engineers how to use optimization theory to solve complex problems with a minimum of mathematics and unifies the large field of optimization with a few geometric principles.
Book

Problems of relative growth

Julian Huxley
TL;DR: This detailed study of the different rates of growth of parts of the body relative to the body as a whole represents Sir Julian Huxley's great contribution to analytical morphology, and it is still a basis for modern investigations in morphometrics and evolutionary biology.
Book

Membrane Computing: An Introduction

Gheorghe Paun
TL;DR: This chapter discusses Membrane Computing, What It Is and What It is Not, and attempts to get back to reality with open problems and Universality results.
Book

Exploring Complexity: An Introduction

TL;DR: Exploring Complexity as discussed by the authors surveys a wide range of complex phenomena arising in the framework of physico-chemical and biological systems and in the global environment and defines the elements of a new scientific vocabulary -the vocabulary of complexity -and elaborates the tools for analyzing these problems efficiently.
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