- author = "Shiny Duela J and Umamageswari A and Prabavathi R and Prashanth Umapathy and Raja K",
- booktitle = "2023 Third International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT)",
- title = "Quantum assisted Genetic Algorithm for Sequencing Compatible Amino Acids in Drug Design",
- year = "2023",
- month = "5-6 " # jan,
- address = "Bhilai, India",
- keywords = "genetic algorithms, genetic programming, Drugs, Proteins, Sequential analysis, Qubit, Quantum mechanics, Genomics, Logic gates, Quantum genetic algorithm, Quantum computing, Qubit encoding, Drug design",
-
DOI = "
doi:10.1109/ICAECT57570.2023.10117673",
- size = "7 pages",
- abstract = "Using quantum computing for drug design is among the most promising applications in quantum technologies. Genetic algorithms with their evolutionary iterations make it a propitious approach in various tasks, including drug discovery, gene prediction, docking of ligands to receptors, and the design to combinatorial libraries. As its computational power and methods limits classical computing, quantum computing intends to break these limits with exponential computing capabilities. This application complements both quantum theory and genetic programming as we use true randomness with mutation and fitness function based on information encoded onto qubits storing quantum data. In this article, we present the results of encoding quantum data to our quantum genetic algorithm, which predicts the best possible drug structure to bind onto the target protein. The qubits hold the genome structure to perform bit string mutation over quantum gates. These results are later than compared to classical computing with various approaches in the evolutionary algorithm parameters.",
-
notes = "Also known as \cite{10117673}
Department of Computer Science and Engineering, SRM Institute of Science and Technology, Ramapuram Campus, Chennai, India",
