Abstract:
The Cell is the most important part of the human body, many small entities and molecules are encapsulated within a cell; shielded by the cell membrane. Proteins are the basic elements within the cell that are responsible for various functionalities, like nutrients across membrane and molecule, identification of foreign bodies, etc. Membrane proteins play a very important function in predicting diseases. Due to advancements in the Next-generation Sequencing, membrane proteins dataset is ever increasing. The experimental methods for the classification of these proteins are very expensive and time-consuming. In this study, prediction about the membrane proteins and its subtypes will be made based on a computational approach using protein primary sequence and machine learning algorithm. For the purpose of more improvement we used the convolutional neural network inception v3 model. The results exhibit the effectiveness of predictive performance as compared to the other existing algorithm.
Some useful techniques are described to make the study more effective.
