Prediction of Lysosomal Membrane Proteins using Machine Learning Techniques

Abstract

With the advancements in the field of protein sequencing techniques, we have entered in the era of proteomics which is an important part of bioinformatics studies. The existence of public databases with billions of data entries requires a robust analytical approach to represent it with respect to its biological significance. Therefore, computational tools are needed to analyze the collected data in the most efficient manner. For acquiring knowledge from the sequence data, there are different ways to achieve it like classifying the sequence on the basis of its subcellular location or determining the structure and hence the function of specific protein. In this study I have developed a machine-learning based method for prediction of lysosomal membrane proteins. Why Lysosomal Membrane Proteins? To understand Lysosomal membrane proteins firstly we have to know what Lysosomes are. Lysosomes are membrane-enclosed organelles that contain an array of enzymes capable of breaking down all types of biological polymers—proteins, nucleic acids, carbohydrates, and lipids. Lysosomes function as the digestive system of the cell, serving both to degrade material taken up from outside the cell and to digest obsolete components of the cell itself. In their simplest form, lysosomes are visualized as dense spherical vacuoles, but they can display considerable variation in size and shape as a result of differences in the materials that have been taken up for digestion. Lysosomes thus represent morphologically diverse organelles defined by the common function of degrading intracellular material.