Using Automated Reasoning Systems on Molecular Computing

This paper is focused on the interplay between automated reasoning systems (as theoretical and formal devices to study the correctness of a program) and DNA computing (as practical devices to handle DNA strands to solve classical hard problems with laboratory techniques). To illustrate this work we have proven in the PVS proof checker, the correctness of a program, in a sticker based model for DNA computation, solving the pairwise disjoint families problem. Also we introduce the formalization of the Floyd–Hoare logic for imperative programs

BioSystems 97 (2009) 146–153 Contents lists available at ScienceDirect

journal homepage: www.elsevier.com/locate/biosystems A novel generalized design methodology and realization of Boolean operations using DN

DNA Cryptography and Deep Learning using Genetic Algorithm with NW algorithm for Key Generation

Cryptography is not only a science of applying complex mathematics and logic to design strong methods to hide data called as encryption, but also to retrieve the original data back, called decryption. The purpose of cryptography is to transmit a message between a sender and receiver such that an eavesdropper is unable to comprehend it. To accomplish this, not only we need a strong algorithm, but a strong key and a strong concept for encryption and decryption process. We have introduced a concept of DNA Deep Learning Cryptography which is defined as a technique of concealing data in terms of DNA sequence and deep learning. In the cryptographic technique, each alphabet of a letter is converted into a different combination of the four bases, namely; Adenine (A), Cytosine (C), Guanine (G) and Thymine (T), which make up the human deoxyribonucleic acid (DNA). Actual implementations with the DNA don’t exceed laboratory level and are expensive. To bring DNA computing on a digital level, easy and effective algorithms are proposed in this paper. In proposed work we have introduced firstly, a method and its implementation for key generation based on the theory of natural selection using Genetic Algorithm with Needleman-Wunsch (NW) algorithm and Secondly, a method for implementation of encryption and decryption based on DNA computing using biological operations Transcription, Translation, DNA Sequencing and Deep Learning.</p

Thermodynamic simulation of deoxyoligonucleotide hybridization, polymerization, and ligation

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1997.Includes bibliographical references (leaves 54-55).by Alexander J. Hartemink.M.S

DNA Oligomers - From Protein Binding to Probabilistic Modelling

This dissertation focuses on rationalised DNA design as a tool for the discovery and development of new therapeutic entities, as well as understanding the biological function of DNA beyond the storage of genetic information. The study is comprised of two main areas of study: (i) the use of DNA as a coding unit to illustrate the relationship between code-diversity and dynamics of self-assembly; and (ii) the use of DNA as an active unit that interacts and regulates a target protein. In the study of DNA as a coding unit in code-diversity and dynamics of self-assembly, we developed the DNA-Based Diversity Modelling and Analysis (DDMA) method. Using Polymerase Chain Reaction (PCR) and Real Time Polymerase Chain Reaction (RT-PCR), we studied the diversity and evolution of synthetic oligonucleotide populations. The manipulation of critical conditions, with monitoring and interpretation of their effects, lead to understanding how PCR amplification unfolding could reshape a population. This new take on an old technology has great value for the study of: (a) code-diversity, convenient in a DNA-based selection method, so semi-quantitation can evaluate a selection development and the population\'s behaviour can indicate the quality; (b) self-assembly dynamics, for the simulation of a real evolution, emulating a society where selective pressures direct the population's adaptation; and (c) development of high-entropy DNA structures, in order to understand how similar unspecific DNA structures are formed in certain pathologies, such as in auto-immune diseases. To explore DNA as an active unit in Tumour Necrosis Factor α (TNF-α) interaction and activity modulation, we investigate DNA's influence on its spatial conformation by physical environment regulation. Active TNF-α is a trimer and the protein-protein interactions between its monomers are a promising target for drug development. It has been hypothesised that TNF-α forms a very intricate network after its activation between its subunits and receptors, but the mechanism is still not completely clear. During our research, we estimate the non-specific DNA binding to TNF-α in the low micro-molar range. Cell toxicity assays confirm this interaction, where DNA consistently enhances TNF-α's cytotoxic effect. Further binding and structural studies lead to the same conclusion that DNA binds and interferes with TNF-α structure. From this protein-DNA interaction study, a new set of tools to regulate TNF-α's biological activity can be developed and its own biology can be unveiled

Design rationnel de nanothermomètres programmables à base d’ADN

Développer de nouveaux nanomatériaux, interrupteurs et machines nanométriques sensibles à de petites variations de température spécifiques devrait être de grande utilité pour une multitude de domaines œuvrant dans la nanotechnologie. De plus, l’objectif est de convaincre le lecteur que les nanotechnologies à base d’ADN offrent d’énormes possibilités pour la surveillance de température en temps réel à l’échelle nanométrique. Dans la section Résultats, nous exploitons les propriétés de l’ADN pour créer des thermomètres versatiles, robustes et faciles à employer. En utilisant une série de nouvelles stratégies inspirées par la nature, nous sommes en mesure de créer des nanothermomètres d’ADN capables de mesurer des températures de 25 à 95°C avec une précision de <0.1°C. En créant de nouveaux complexes d’ADN multimériques, nous arrivons à développer des thermomètres ultrasensibles pouvant augmenter leur fluorescence 20 fois sur un intervalle de 7°C. En combinant plusieurs brins d’ADN avec des plages dynamiques différentes, nous pouvons former des thermomètres montrant une transition de phase linéaire sur 50°C. Finalement, la vitesse de réponse et la précision des thermomètres développés et leur réversibilité sont illustrées à l’aide d’une expérience de surveillance de température à l’intérieur d’un unique puits d’un appareil de qPCR. En conclusion, les applications potentielles de tels nanothermomètres en biologie synthétique, imagerie thermique cellulaire, nanomachines d’ADN et livraison contrôlée seront considérées.Developing nanomaterials, probes, switches or nanomachines that are able to respond to specific temperature changes should prove of utility for several applications in the fields of in vivo imaging, clinical diagnostics, and drug-delivery. Here, we describe various bio- inspired strategies to engineer DNA thermoswitches with programmable linear response ranges for precise temperature sensing between 25 to 95°C with thermal precision <0.1°C. Using multimeric switch architectures, we are able to create ultrasensitive thermometers that display large 20-fold, quantitative signal changes within only 7°C. Lastly, by combining thermoswitches of different stabilities, or a mix of stabilizers of various strengths, we can create extended thermometers that respond linearly in a 50°C temperature window. Using these programmable DNA thermometers we measured, for the first time, the temperature equilibration time inside PCR wells using a fluorescent readout. Their potential applications in in vivo imaging, DNA nanomachines, drug delivery systems and synthetic biology are further discussed