Analysis of Protein Structure for Drug Repurposing Using Computational Intelligence and ML Algorithm

1. Introduction

Data mining techniques are incredibly large data sets that investigate trends, patterns, and classify information based on computer investigations. Data Mining is produced as a result of the rapid growth of data, which enables the acquisition of knowledge and the extraction of significant data.

Prediction of protein secondary structure is a fundamental procedure in protein science, whereas computational biology is used to recognize protein three-dimensional structures in order to uncover organic functions¹. Protein sequencing technologies aid in the identification of disease-causing genetic variants. This involves the analysis of a massive quantity of sequencing data to aid computational approaches in efficiently discovering the subset of disease-related variants. The extraction of information from the DNA sequence of an organism is important for both biological study and medical applications.

Figure 1.

Breast cancer classifications

1.3 Machine Learning for Bio- Medical Data

Computer-assisted learning (CALM) is a hybrid of AI and computational intelligence. Intelligent machines capable of resolving real-world issues will be modelled like human minds, according to these researchers^{2, 3}. Genetic algorithms, belief networks, and learning theory are a few examples of probabilistic reasoning. In order to design, develop, and implement intelligent discovery, these factors must be taken into consideration.

Figure 2.

Connections between Medical Informatics, Medicine data, and Protein Structure