Algorithmic Bioprocesses
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Algorithmic Bioprocesses

 eBook
Sofort lieferbar | Lieferzeit: Sofort lieferbar I
ISBN-13:
9783540888697
Veröffentl:
2009
Einband:
eBook
Seiten:
742
Autor:
Anne Condon
Serie:
Natural Computing Series
eBook Typ:
PDF
eBook Format:
Reflowable eBook
Kopierschutz:
Digital Watermark [Social-DRM]
Sprache:
Englisch
Beschreibung:

A fundamental understanding of algorithmic bioprocesses is key to learning how information processing occurs in nature at the cell level. Written by the leading researchers in this area, this is the first book to examine this subject comprehensively.

A fundamental understanding of algorithmic bioprocesses is key to learning how information processing occurs in nature at the cell level. The field is concerned with the interactions between computer science on the one hand and biology, chemistry, and DNA-oriented nanoscience on the other. In particular, this book offers a comprehensive overview of research into algorithmic self-assembly, RNA folding, the algorithmic foundations for biochemical reactions, and the algorithmic nature of developmental processes.

The editors of the book invited 36 chapters, written by the leading researchers in this area, and their contributions include detailed tutorials on the main topics, surveys of the state of the art in research, experimental results, and discussions of specific research goals. The main subjects addressed are sequence discovery, generation, and analysis; nanoconstructions and self-assembly; membrane computing; formal models and analysis; process calculi and automata; biochemical reactions; and other topics from natural computing, including molecular evolution, regulation of gene expression, light-based computing, cellular automata, realistic modelling of biological systems, and evolutionary computing.

This subject is inherently interdisciplinary, and this book will be of value to researchers in computer science and biology who study the impact of the exciting mutual interaction between our understanding of bioprocesses and our understanding of computation.

Tribute.- Grzegorz Rozenberg: A Magical Scientist and Brother.- Sequence Discovery, Generation, and Analysis.- Monotony and Surprise.- Information Content of Sets of Biological Sequences Revisited.- Duplication in DNA Sequences.- Sequence and Structural Analyses for Functional Non-coding RNAs.- Gene Assembly in Ciliates.- Strategies for RNA-Guided DNA Recombination.- Reality-and-Desire in Ciliates.- Template-Guided Recombination: From Theory to Laboratory.- Nanoconstructions and Self-assembly.- DNA Cages with Icosahedral Symmetry in Bionanotechnology.- Applying Symmetric Enumeration Method to One-Dimensional Assembly of Rotatable Tiles.- A Self-assembly Model of Time-Dependent Glue Strength.- The Perils of Polynucleotides Revisited.- Algorithmic Control: The Assembly and Operation of DNA Nanostructures and Molecular Machinery.- Membrane Computing.- On Nonuniversal Symport/Antiport P Systems.- Spiking Neural P Systems. Recent Results, Research Topics.- Membrane Computing Schema: A New Approach to Computation Using String Insertions.- Formal Models and Analysis.- Finite Splicing: Generative Capacity, New Models and Complexity Aspects.- Formal Models of the.- Understanding Network Behavior by Structured Representations of Transition Invariants.- Quantitative Verification Techniques for Biological Processes.- A New Mathematical Model for the Heat Shock Response.- Process Calculi and Automata.- Artificial Biochemistry.- Process Calculi Abstractions for Biology.- Deriving Differential Equations from Process Algebra Models in Reagent-Centric Style.- Programmable DNA-Based Finite Automata.- Biochemical Reactions.- A Multi-volume Approach to Stochastic Modeling with Membrane Systems.- Programmability of Chemical Reaction Networks.- Log-gain Principles forMetabolic P Systems.- Hybrid Method for Simulating Small-Number Molecular Systems.- Broader Perspective.- On Involutions Arising from Graphs.- Parallel Computing by Xeroxing on Transparencies.- Some Undecidable Dynamical Properties for One-Dimensional Reversible Cellular Automata.- On Using Divide and Conquer in Modeling Natural Systems.- No Molecule Is an Island: Molecular Evolution and the Study of Sequence Space.- Niching Methods: Speciation Theory Applied for Multi-modal Function Optimization.- On the Concept of -regulatory Information: From Sequence Motifs to Logic Functions.

A fundamental understanding of algorithmic bioprocesses is key to learning how information processing occurs in nature at the cell level. The field is concerned with the interactions between computer science on the one hand and biology, chemistry, and DNA-oriented nanoscience on the other. In particular, this book offers a comprehensive overview of research into algorithmic self-assembly, RNA folding, the algorithmic foundations for biochemical reactions, and the algorithmic nature of developmental processes.

The editors of the book invited 36 chapters, written by the leading researchers in this area, and their contributions include detailed tutorials on the main topics, surveys of the state of the art in research, experimental results, and discussions of specific research goals. The main subjects addressed are sequence discovery, generation, and analysis; nanoconstructions and self-assembly; membrane computing; formal models and analysis; process calculi and automata; biochemical reactions; and other topics from natural computing, including molecular evolution, regulation of gene expression, light-based computing, cellular automata, realistic modelling of biological systems, and evolutionary computing.

This subject is inherently interdisciplinary, and this book will be of value to researchers in computer science and biology who study the impact of the exciting mutual interaction between our understanding of bioprocesses and our understanding of computation.

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