Systems biology and the origins of life? Part I. Are biochemical networks possible ancestors of living systems? Reproduction, identity and sensitivity to signals of biochemical networks

The SBML (systems biology markup language) is a standard exchange format for computational models of biochemical networks. We continue developing SBML collaboratively with the modelling community to meet their evolving needs. The recently introduced SBML Level 2 includes several enhancements to the original Level 1, and features under development for SBML Level 3 include model composition, multistate chemical species and diagrams.

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Systems Biology and Infectious Diseases

Handbook of Research on Systems Biology Applications in Medicine ◽

10.4018/978-1-60566-076-9.ch023 ◽

2009 ◽

pp. 377-402 ◽

Cited By ~ 1

Author(s):

Alia Benkahla ◽

Lamia Guizani-Tabbane ◽

Ines Abdeljaoued-Tej ◽

Slimane Ben Miled ◽

Koussay Dellagi

Keyword(s):

Immune Response ◽

Systems Biology ◽

Molecular Biology ◽

Infected Cell ◽

Regulatory Networks ◽

Interdisciplinary Approach ◽

Biochemical Networks ◽

Mathematical Methods ◽

Meaningful Information ◽

Models And Modelling

This chapter reports a variety of molecular biology informatics and mathematical methods that model the cell response to pathogens. The authors first outline the main steps of the immune response, then list the high throughput biotechnologies, generating a wealth of information on the infected cell and some of the immune-related databases; and finally explain how to extract meaningful information from these sources. The modelling aspect is divided into modelling molecular interaction and regulatory networks, through dynamic Boolean and Bayesian models, and modelling biochemical networks and regulatory networks, through Differential/Difference Equations. The interdisciplinary approach explains how to construct a model that mimics the cell’s dynamics and can predict the evolution and the outcome of infection.

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Erratum to: ‘Conditional robustness analysis for fragility discovery and target identification in biochemical networks and in cancer systems biology’

BMC Systems Biology ◽

10.1186/s12918-016-0267-2 ◽

2016 ◽

Vol 10 (1) ◽

Author(s):

Fortunato Bianconi ◽

Elisa Baldelli ◽

Vienna Ludovini ◽

Emanuel F. Petricoin ◽

Lucio Crinò ◽

...

Keyword(s):

Systems Biology ◽

Target Identification ◽

Robustness Analysis ◽

Biochemical Networks ◽

Cancer Systems Biology

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Deciphering the regulation mechanism in biochemical networks by a systems-biology approach

10.1101/203901 ◽

2017 ◽

Author(s):

Bernardo A. Mello ◽

Yuhai Tu

Keyword(s):

Systems Biology ◽

Molecular Mechanisms ◽

Biochemical Networks ◽

System Level ◽

Regulation Mechanism ◽

Input Output ◽

Output Data ◽

Data Set ◽

Complex Processes ◽

Regulation Mechanisms

To decipher molecular mechanisms in biological systems from system-level input-output data is challenging especially for complex processes that involve interactions among multiple components. Here, we study regulation of the multi-domain (P1-5) histidine kinase CheA by the MCP chemoreceptors. We develop a network model to describe dynamics of the system treating the receptor complex with CheW and P3P4P5 domains of CheA as a regulated enzyme with two substrates, P1 and ATP. The model enables us to search the hypothesis space systematically for the simplest possible regulation mechanism consistent with the available data. Our analysis reveals a novel dual regulation mechanism wherein besides regulating ATP binding the receptor activity has to regulate one other key reaction, either P1 binding or phosphotransfer between P1 and ATP. Furthermore, our study shows that the receptors only control kinetic rates of the enzyme without changing its equilibrium properties. Predictions are made for future experiments to distinguish the remaining two dual-regulation mechanisms. This systems-biology approach of combining modeling and a large input-output data-set should be applicable for studying other complex biological processes.

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SABIO-RK: A data warehouse for biochemical reactions and their kinetics

Journal of Integrative Bioinformatics ◽

10.1515/jib-2007-49 ◽

2007 ◽

Vol 4 (1) ◽

pp. 22-30 ◽

Cited By ~ 6

Author(s):

Olga Krebs ◽

Martin Golebiewski ◽

Renate Kania ◽

Saqib Mir ◽

Jasmin Saric ◽

...

Keyword(s):

Systems Biology ◽

Kinetic Data ◽

Biochemical Networks ◽

System Level ◽

Kinetic Properties ◽

Biological Processes ◽

Biochemical Reactions ◽

Biochemical Pathways ◽

Application Potential ◽

Promising Application

Abstract Systems biology is an emerging field that aims at obtaining a system-level understanding of biological processes. The modelling and simulation of networks of biochemical reactions have great and promising application potential but require reliable kinetic data. In order to support the systems biology community with such data we have developed SABIO-RK (System for the Analysis of Biochemical Pathways - Reaction Kinetics), a curated database with information about biochemical reactions and their kinetic properties, which allows researchers to obtain and compare kinetic data and to integrate them into models of biochemical networks. SABIO-RK is freely available for academic use at http://sabio.villa-bosch.de/SABIORK/.

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Prebiotic Geochemical Automata at the Intersection of Radiolytic Chemistry, Physical Complexity, and Systems Biology

Complexity ◽

10.1155/2018/9376183 ◽

2018 ◽

Vol 2018 ◽

pp. 1-21 ◽

Cited By ~ 1

Author(s):

Zachary R. Adam ◽

Albert C. Fahrenbach ◽

Betul Kacar ◽

Masashi Aono

Keyword(s):

Systems Biology ◽

Living Systems ◽

Organizational Attributes ◽

Exchange Processes ◽

History Of ◽

Prebiotic Molecules ◽

Far From Equilibrium ◽

Chemical Conditions ◽

Equilibrium Chemical ◽

Object Level

The tractable history of life records a successive emergence of organisms composed of hierarchically organized cells and greater degrees of individuation. The lowermost object level of this hierarchy is the cell, but it is unclear whether the organizational attributes of living systems extended backward through prebiotic stages of chemical evolution. If the systems biology attributes of the cell were indeed templated upon prebiotic synthetic relationships between subcellular objects, it is not obvious how to categorize object levels below the cell in ways that capture any hierarchies which may have preceded living systems. In this paper, we map out stratified relationships between physical components that drive the production of key prebiotic molecules starting from radiolysis of a small number of abundant molecular species. Connectivity across multiple levels imparts the potential to create and maintain far-from-equilibrium chemical conditions and to manifest nonlinear system behaviors best approximated using automata formalisms. The architectural attribute of “information hiding” of energy exchange processes at each object level is shared with stable, multitiered automata such as digital computers. These attributes may indicate a profound connection between the system complexity afforded by energy dissipation by subatomic level objects and the emergence of complex automata that could have preceded biological systems.

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Mathematical Methods in Modelling Biochemical Networks in Systems Biology

Series on Advances in Bioinformatics and Computational Biology - Computational Systems Biology of Synaptic Plasticity ◽

10.1142/9781786343383_0002 ◽

2017 ◽

pp. 19-85

Keyword(s):

Systems Biology ◽

Biochemical Networks ◽

Mathematical Methods

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Mechanical Energy before Chemical Energy at the Origins of Life?

Sci ◽

10.3390/sci1020050 ◽

2019 ◽

Vol 1 (2) ◽

pp. 50

Author(s):

Helen Greenwood Hansma

Keyword(s):

Mechanical Energy ◽

Living Cells ◽

Origins Of Life ◽

Heat Pumps ◽

Chemical Energy ◽

Living Systems ◽

Prebiotic Environments ◽

Response To Water

Forces and mechanical energy are prevalent in living cells. This may be because forces and mechanical energy preceded chemical energy at life’s origins. Mechanical energy is more readily available in non-living systems than the various other forms of energy used by living systems. Two possible prebiotic environments that might have provided mechanical energy are hot pools that experience wet/dry cycles and mica sheets as they move, open and shut, as heat pumps or in response to water movements.

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