Petri Net Recommender System to Model Metabolic Pathway of Polyhydroxyalkanoates

Sakshi Gupta, Gajendra Pratap Singh and Sunita Kumawat
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Sakshi Gupta: Amity University Haryana, Gurugram, India
Gajendra Pratap Singh: School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi, India
Sunita Kumawat: Amity University Haryana, Gurugram, India

International Journal of Knowledge and Systems Science (IJKSS), 2019, vol. 10, issue 2, 42-59

Abstract: Due to the complexity of the metabolic pathways, their modeling has been a great challenge for the researchers. Various mathematical models have been developed and are continuing to be developed to model and study metabolic pathways. In this article, the authors have described Petri nets (PNs) as a recommender system to model one of the metabolic pathways of Polyhydroxyalkanoates. Recommender systems have become an integral part of today's world. Their applications lie in the fields of e-commerce, bioinformatics and many more. Petri nets are one of the promising mathematical tools which can be treated as a recommender system to model and analyze the complex metabolic pathways of various organisms because of the representation of these pathways as graphs. The PN toolbox validates the obtained Petri net model. Polyhydroxyalkanoates, commonly known as PHAs, are biodegradable microbial polyesters and have properties quite similar to commonly used non-biodegradable plastics. Due to their biodegradability, biocompatibility, and eco-friendly nature, they are of biological significance and are used in various applications in wide range of sectors like medical sector, drug delivery, tissue engineering, and many more. The obtained PN model of Polyhydroxyalkanoates has been validated using PN toolbox.

Date: 2019
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