Ozan Emre EYUPOGLU

Istanbul Medipol University, Turkey

Title: Algorithmic Signalling Controlling Enzymatic Catalysis with Artificial Intelligence Robotic Approach

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Biography

Ozan Emre Eyupoglu is an Assistant Professor in School of Pharmacy at Istanbul Medipol University, ?stanbul, Turkey He received his PhD Degree from Graduate School of Natural & Applied Sciences, Chemistry (Biochemistry), Karadeniz Technical University, Turkey in 2017. His area of interest includes Health Sciences, Medicine, Basic Medical Sciences, Biochemistry, Biophysics, Biomolecules, Proteomics and Biological Spectroscopy. He has published number of researches and conference articles about the chromatographic analysis and antioxidant activities of medicinal plants in reputed journals. He is closely related to topics such as artificial intelligence, machine learning, and innovative techniques, and plans studies for processing biochemical data for disease diagnosis. He is an interdisciplinary scientist who specializes in developing on-line chromatographic methods. He supervised 2 Master degree candidates who are making thesis on the coagulation system and aromatherapy recently.

Abstract

Bioregulation can be controlled by monitoring the frequency of the 3x3 matrix code produced by artificial intelligence with an algorithm that combines the state-of-the-art learning algorithm with the enzyme pathway signalling mechanisms. Computations powered by algorithmic advances enable the generation and verification of realistic models that can be used to reveal new enzymatic catalysis mechanisms. By using algorithmic tools for horizontal and vertical asymptotic analysis, enzymatic catalysis is regulated with a wide range of parameters in dimensional form with measurement precision. Enzymes are transformed into biogenic robots with the signals sent to the biocatalyst, which maintains the enzymatic activity in the form of a continuous Markov chain ring by the parallel replication method by accelerating the stochastic reaction networks of the sinusoidal distribution. Rational catalyst design is determined by measuring the free energy changes in the Hamiltonian catalytic mechanism. Using programmable logic, Hamiltonian design defines free energy changes related to catalytic activity and input variables can be suggested by making uncertainty estimates. When the thermodynamic and kinetic parameters of the reaction mechanism calculated using empirical quantum chemistry are taken into account, enzymatic activity is achieved by jumps in small energy changes. As a result of the study, programmable bionic robot enzymes were created by combining quantum mechanics and Hamiltonian design and using free energy jumps. 

Keywords: Enzymatic Catalysis, Artificial Intelligence, Robotic Algorithm, Signal transmission.