DNA computing

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This work explores various aspects of biomolecular computing and DNA manipulation, detailing innovative approaches and experimental validations. It covers self-correcting self-assembly growth models and the Hammersley process, along with the recognition of DNA splicing and computational properties of template-guided DNA recombination. The text discusses practical applications of biomolecular computers through microfluidic deoxyribozyme logic gate networks and presents methods for DNA recombination via XPCR. Key topics include an algorithm for SAT without an extraction phase, sensitivity and capacity of microarray encodings, and simple operations for gene assembly. The work also examines bounded symport/antiport P systems and the expectation and variance of self-assembled graph structures. It delves into hairpin structures in DNA words and efficient algorithms for testing structure freeness in biomolecular sequences. Additionally, it highlights communicating distributed H systems, intensive in vitro experiments for finite automata, and the development of in vivo computers based on Escherichia coli. Techniques for controlling DNA molecules using optical methods and the design of nucleotide sequences for computation are discussed, alongside analyses of DNA nanomachines and microfluidic devices for self-assembly. The complexity of graph self-assembly and molecular learning of wDNF formulae are also examined, showcasing the inter