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  1. Proceedings of the 8th International Conference on Computational Methods in Systems Biology (CMSB '10)
  2. Building cell-like structures from the bottom-up
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From species to pathway and tissue as process
Building cell-like structures from the bottom-up
Discrete causal model view of biological networks
Steady-state solution of biochemical systems, beyond S-systems via T-invariants
On verifying Bio-PEPA models
Target driven biochemical network reconstruction based on petri nets and simulated annealing
A generic abstract machine for stochastic process calculi
Hybrid numerical solution of the chemical master equation
Action-based analysis of discrete regulatory networks with short-term stimuli
Stochasticity in reactions: a probabilistic Boolean modeling approach
Understanding signalling networks as collections of signal transduction pathways
A comparative study of stochastic analysis techniques
Structural identification of GMA models: algorithm and model comparison

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Building cell-like structures from the bottom-up

Content Provider ACM Digital Library
Author Mansy, Sheref S.
Abstract It is a commonly held view that life's inherent complexity renders its construction futile. The simplest known microorganisms possess hundreds of apparently essential genes, many of which provide unknown functionality. For this and other reasons, attempts to engineer cells with desired functionality have focused on using existing organisms as a chassis for the incorporation of desired traits. While informative, these approaches are limited by the complex evolutionary history of life. For example, a complicated path of evolutionary change, including lateral gene transfers and genetic reductions tailored to specific environmental niches, has occurred for all organisms. This complexity masks the simple physical and chemical forces that underlie life-like processes. Recently, much evidence has accumulated showing that chemical-physical forces alone, in the absence of complex biological machinery, can give rise to the life-like processes of growth, division, replication, and nutrient acquisition. By combining the lessons learned from such studies with a few key biological components, we hope to build drastically simplified and robust cell-like structures.
Starting Page 3
Ending Page 3
Page Count 1
File Format PDF
ISBN 9781450300681
DOI 10.1145/1839764.1839766
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2010-09-29
Publisher Place New York
Access Restriction Subscribed
Content Type Text
Resource Type Article
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