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VAWKUM Transaction on Computer Sciences
Number of Followers: 1

This is an Open Access Journal

Open Access journal
ISSN (Print) 2308-8168 - ISSN (Online) 2308-8168
Published by Virtual Foundation for Advancement of Science and Technology

[2 journals]

Analyzing updates in Amino Acid Composition and Translation Algorithm
towards Predicting Membrane Proteins using Machine Learning Approaches
- Authors: Abdulsalam Mohammed Alfarsi, Abdulrahman Mohammed Alghanmi
  Abstract: Membrane proteins are of different types that take on different functions. Classification of protein sequences in a data set is very important for understanding cell functions, disease prevention, and drug discovery. Initially, traditional methods were used for transmembrane protein classification. However, due to advanced technology and new research, it increases the transmembrane protein datasets by thousands which are almost impossible to obtain accurate results based on traditional methods. Computational methods are very useful for membrane protein classification. Several methods such as Pseudo Amino Acid Composition (PseAAC) can extract many silent features of a protein sequence. In this work, we intended to modify an existing algorithm of amino acid composition and translation to extract membrane protein features with better accuracy. To validate our algorithm, we will use the Support Vector Machine SVM and KNN.
  PubDate: 2022-03-28
  Issue No: Vol. 9 (2022)
K-Nearest Neighbor Classifier for Classifying user Reviews on Social Media
Networks
- Authors: Fahad Alotaibi, Nashwan Ahmed Alromema
  Abstract: Gigantic content generated on social media networking sites have made the online users enabled to communicate their opinions and sentiments about products and other entities like political events etc. Opinion mining applications aim to provide facilities to user and companies for know about products in which they are interested. In this work, opinion mining system for comparative reviews is developed using supervised machine learning approach. For this purpose, K-nearest neighbor classifier is trained on a publicly available dataset. Effectiveness of the system is validated by comparing its performance with other classifiers.
  PubDate: 2022-10-15
  Issue No: Vol. 10 (2022)

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