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Biological computing
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Biological computing/ by Jin Xu.
作者:
Xu, Jin.
出版者:
Singapore :Springer Nature Singapore : : 2025.,
面頁冊數:
xvii, 329 p. :ill. (chiefly color), digital ; : 24 cm.;
Contained By:
Springer Nature eBook
標題:
Hardware Performance and Reliability. -
電子資源:
https://doi.org/10.1007/978-981-96-3870-3
ISBN:
9789819638703
Biological computing
Xu, Jin.
Biological computing
[electronic resource] /by Jin Xu. - Singapore :Springer Nature Singapore :2025. - xvii, 329 p. :ill. (chiefly color), digital ;24 cm.
Chapter 1 Introduction -- Chapter 2 Graphs and Computational Complexity -- Chapter 3 Biocomputing -- Data -- Chapter 4 Biological Computing Operators -- Enzymes and Biochemical Operations -- Chapter 5 DNA Coding Theory and Algorithms -- Chapter 6 Enumerative DNA Computing Model -- Chapter 7 Non-enumerative DNA Computing Model for Graph Vertex Coloring -- Chapter 8 Parallel Vertex Coloring DNA Computing Model -- Chapter 9 Probe Machine -- Chapter 10 DNA Algorithmic Self-Assembly -- Chapter 11 RNA Computing -- Chapter 12 Protein Computing.
Open access.
This open access book comprehensively introduces biocomputing, focusing on its foundational theories, experimental operations, and computational models. Biocomputing represents an innovative computational paradigm that leverages biomolecules as a carrier for processing and storing information. As a core enabler of human progress, computational tools serve as critical benchmarks of societal advancement and are key drivers of technological innovation. While electronic computers currently dominate as the primary instruments for information processing, their underlying manufacturing technologies are approaching physical and practical limits. This has prompted the search for alternative computational models and tools to meet the demands of future advancements. Over recent decades, scientists have explored various fields to develop novel computational frameworks. These efforts have led to the emergence of groundbreaking paradigms, such as artificial neural networks inspired by brain-like information processing, evolutionary computing based on genetic mechanisms, biocomputing utilizing the unique properties of biomolecules, quantum computing exploiting quantum phenomena, and optical computing leveraging the properties of light. Designed as an essential resource for readers interested in the principles and applications of biocomputing, this book establishes a foundational understanding of the subject while serving as a bridge to more advanced theoretical and practical exploration. A basic knowledge of molecular biology is recommended for readers to engage with the material fully. The translation was done using artificial intelligence. Subsequently, a human revision was done primarily in terms of content.
ISBN: 9789819638703
Standard No.: 10.1007/978-981-96-3870-3doiSubjects--Topical Terms:
1366872
Hardware Performance and Reliability.
LC Class. No.: QA76.884
Dewey Class. No.: 006.3842
Biological computing
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Chapter 1 Introduction -- Chapter 2 Graphs and Computational Complexity -- Chapter 3 Biocomputing -- Data -- Chapter 4 Biological Computing Operators -- Enzymes and Biochemical Operations -- Chapter 5 DNA Coding Theory and Algorithms -- Chapter 6 Enumerative DNA Computing Model -- Chapter 7 Non-enumerative DNA Computing Model for Graph Vertex Coloring -- Chapter 8 Parallel Vertex Coloring DNA Computing Model -- Chapter 9 Probe Machine -- Chapter 10 DNA Algorithmic Self-Assembly -- Chapter 11 RNA Computing -- Chapter 12 Protein Computing.
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This open access book comprehensively introduces biocomputing, focusing on its foundational theories, experimental operations, and computational models. Biocomputing represents an innovative computational paradigm that leverages biomolecules as a carrier for processing and storing information. As a core enabler of human progress, computational tools serve as critical benchmarks of societal advancement and are key drivers of technological innovation. While electronic computers currently dominate as the primary instruments for information processing, their underlying manufacturing technologies are approaching physical and practical limits. This has prompted the search for alternative computational models and tools to meet the demands of future advancements. Over recent decades, scientists have explored various fields to develop novel computational frameworks. These efforts have led to the emergence of groundbreaking paradigms, such as artificial neural networks inspired by brain-like information processing, evolutionary computing based on genetic mechanisms, biocomputing utilizing the unique properties of biomolecules, quantum computing exploiting quantum phenomena, and optical computing leveraging the properties of light. Designed as an essential resource for readers interested in the principles and applications of biocomputing, this book establishes a foundational understanding of the subject while serving as a bridge to more advanced theoretical and practical exploration. A basic knowledge of molecular biology is recommended for readers to engage with the material fully. The translation was done using artificial intelligence. Subsequently, a human revision was done primarily in terms of content.
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