Machine Learning Applications for Plant Biotechnology: Modeling of The Plant Tissue Culture Procedures with Artificial Neural Networks

Abstract

Developments in biotechnology and information technologies have increased exponentially in recent years, and thanks to this progress, it is possible to develop functional experimental technologies. With the acceleration of biotechnological developments, it is becoming more and more practical, fast, and easy to design, develop and implement experimental studies. Experimental studies in recent years have the potential to produce a large amount of data that will allow the necessary analysis and inferences to be made, and the data obtained are stored in different ways and in many databases. Analyzing the findings obtained by the researchers correctly and making the proper inferences requires that these data and the large amount of information stored in the databases be integrated appropriately into the system. This article offers various perspectives on storing data obtained in vitro plant tissue culture studies, integrating it with data from different sources, obtaining new information, and applying it functionally.