Diagnostic computational model for neuronal disorder through glycogen metabolism in astrocytes. (2018)

• Record Type: Journal Article
• Authors: Selvakumar, R.; Muhammad, M. Rashith
• Is Part Of: International journal of computing science and mathematics. Volume 9:Number 3(2018)
• Page Start: 232
• Page End: 239
• Publication Date: 2018
• Subjects: embedded automaton -- enzymes -- glial cell -- glycogen metabolism; Mathematics -- Periodicals; Computer science -- Periodicals; Mathematics -- Data processing -- Periodicals; 510.285
• Languages: English
• ISSNs: 1752-5055

Abstract

An automaton called embedded automaton is introduced to monitor the glycogen metabolism with an end product as lactate in astrocytes. It is designed to observe the glycogen metabolism with the states of acceptance and rejection. It is a hybridisation of both non–deterministic finite automaton and push–down automaton. The acceptance state of the embedded automaton depicts the normal level of glycogen synthesis and degradation. The rejection state of this machine shows the inhibition of metabolic processes in the absence of active enzymes. The process of glycogen metabolism in astrocytes can be regulated with a group of regulatory enzymes. It assists in enhancing the energy supply to neurons by regulating the neuronal activity. The construction of computational model using automata theory can help in targeting research on the enzymatic activity in brain glycogen pathways. Such an interdisciplinary approach can be a promising therapeutic application for both diagnosis and therapy for neuronal injuries.