Biological Computing

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.

This book is open access, which means that you have free and unlimited access Master biocomputing fundamentals to unlock the potential of biomolecule-based computation Access cutting-edge theories and models to navigate the future of post-electronic computing Learn from an award-winning expert to gain a competitive edge in intelligent computing research

Autorentext

Jin Xu is a tenured professor and PhD supervisor at Peking University, holding dual doctorates in science and engineering. He earned his first Ph.D. from Xi an Jiaotong University in 1993 and the second from Beijing Institute of Technology in 1994. Dr. Xu has published over 200 SCI-indexed papers as the first or corresponding author. His primary research interests encompass graph theory, biological computing, and neural networks. He has also successfully led ten national projects, including those funded by the National Natural Science Foundation (NSFC), some 973 projects, and some 863 projects. Their work has been recognized with numerous prestigious awards, including a Second Prize in the National Natural Science Award, two First Prizes in the Natural Science Award from the Ministry of Education, and a First Prize in the Natural Science Award from Hubei Province.

Inhalt

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.