Design de Circuitos Lógicos Baseados em DNA Visando a Síntese de Sistemas Computacionais

• Ano de defesa: 2018
• Autor(a) principal: Daniel Kneipp de Sá Vieira
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Minas Gerais; UFMG
• Palavras-chave em Português: Computação com DNA; Nanocomputação; Redes de Reações Químicas; Reação de Deslocamento de Cadeia; Computação
• Link de acesso: http://hdl.handle.net/1843/ESBF-BA8NS3

DNA computing is one of the branches of molecular computing that has been used in recent years to develop devices implanted in-vitro, in-vivo or even replace the CMOS technology in some applications. Using a technique known as Strand Replacement Reaction. DNA strands are combined and manipulated in programmatic fashion following a certain logic. This computing model allows us to implement physically theoretical behaviors specified using the Chemical Reaction Networks (CRNs) language, which textually describes the reaction network kinetics. With a language to describe DNA-based devices, building blocks for circuitry development are defined, increasing considerably the complexity of the device and, consequently, simulate these devices becomes difficult. In this dissertation a simulation package for large scale DNA-based devices is presented. It is called DNAr and it was developed to simulate formal CRNs (theoretical reaction networks) and DNA-based CRNs (reactions that represent interactions between DNA molecules). This package also is capable of transforming a formal CRN to a DNA-based CRN without user interference. Well-known CRNS (e.g.: Lotka-Volterra oscillator, Consensus, etc.) were used to validate the simulator. Two case studies were conducted in order to validate and exemplify the DNAr expansion capabilities. These case studies are based on two approaches of chemical logic gates construction. One of them models a logic gate directly while the other has chemical neurons as it building block. Both approaches were implemented as DNAr extensions and they can be used to design other circuits. A logic circuit capable of detecting cancer cells was used as the target circuit to be implemented by these approaches. The results show that both approaches achieved the desired behavior. The fact that CRNs with 200 to 400 reactions were generated indicates the need of a tool such as DNAr