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ABSTRACT
Similarity analysis of protein sequences can expose the evolutionary relationship among them. It is required to design effective computational algorithms that can compare the similarities among the colossal amount of sequences. Alignment-based approaches to this problem are often computationally expensive, especially when the number of sequences is large. This research aims to develop an efficient alignment-free tool in the field of protein sequence comparison and phylogenetic study. The proposed method, namely EightyDVec, performs a feature generation process based on the physiochemical properties of amino acids that best describe the evolutionary relationship among the species in a protein family. Using EightyDVec, protein sequences are transformed into 80-dimensional feature vectors and the comparisons between sequences are performed conveniently through these vectors. Four different datasets are used to validate the accuracy of EightyDVec, and the obtained results have shown the great effectiveness of the proposed method in the similarity analysis of protein sequences.
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No potential conflict of interest was reported by the authors.
Additional information
Notes on contributors
Ranjeet Kumar Rout
Ranjeet Kumar Rout is currently serving as Assistant Professor in the Department of Computer Science and Engineering, National Institute of Technology Srinagar, Hazratbal, India. He received his Ph.D. degree from the Department of Information Technology of Indian Institute of Engineering Science and Technology Shibpur, West Bengal, India in the year 2018. He earned Post Graduate and Bachelor Degree in Computer Science and Engineering from Biju Patnaik University of Technology, Odisha, India, in 2010 and 2005 respectively. Prior to working at NIT Srinagar, Dr. Ranjeet had some useful research and teaching experience from Amity University Noida, National Institute Technology Jalandhar, and Indian Statistical Institute (ISI) Kolkata, India. His research interests include machine learning, and deep learning, visual cryptography and computational biology. He has published several papers in peer-reviewed international and scientific journals in the field of non-linear Boolean functions and computational biology.
Saiyed Umer
Saiyed Umer received B.Sc. (Hons) degree in Mathematics from Vidyasagar University, India, in 2005. He earned a Master of Computer Applications from West Bengal University of Technology, India, in 2008, M.Tech degree from the University of Kalyani, India, in 2012 and Ph.D. from the Department of Information Technology at Jadavpur University, Kolkata, India, respectively. He was the Research Personnel at Indian Statistical Institute (ISI), Kolkata, India, from November 2012 to April 2017. Currently, he has joined as an Assistant Professor in the Department of Computer Science and Engineering, Aliah University, Kolkata, India. His research interests include Biometric, Computer Vision, Machine Learning, and Deep Learning.
Sabha Sheikh
Sabha Sheikh is currently working as Assistant Professor in the Department of Computer Science and Engineering, National Institute of Technology Srinagar. She received her M.Tech in Computer Science Engineering from Jamia Hamdard, New Delhi in 2017 and B.Tech (CSE) from PTU, Jalandhar in 2014. She has published papers in conferences and journals. Her research interests include machine learning, deep learning, image processing, and computational biology.
Sanchit Sindhwani
Sanchit Sindhwani is currently working as Software Development Engineer at Amazon India Development Center, Bengaluru, Karnataka, India. Prior to that, he was working as Software Engineer at Samsung R&D Center, Noida, Uttar Pradesh, India. He has worked on both the Application and Network side of things, working on IMS at Samsung and now for Customer-facing things on well-known E-Commerce. He received his Bachelor from the department of Computer Science and Engineering of Dr. B R Ambedkar National Institute of Technology, Jalandhar, Punjab , India in the year 2018. His research interests include cryptography and computational biology. He has published papers in peer-reviewed international and scientific journals in the field of computational biology and cryptography.
Smitarani Pati
Smitarani Pati received the B. Tech degree in electrical engineering from the Biju Patnaik University of Technology, Odisha, India, in 2011, the M.Tech degree in control and Instrumentation Engineering from Dr. B.R. Ambedkar National Institute of Technology Jalandhar, Punjab, India 2018, and perusing a Ph.D. degree in Instrumentation and Control Engineering from Dr. B.R. Ambedkar National Institute of Technology Jalandhar, Punjab, India. She is a Research Associate in Instrumentation and Control Engineering and actively worked on modeling, control, and optimization of industrial processes such as Energy optimization using soft computing techniques since August 2018. She has published several articles in international conferences and book chapters. Her current research interests include Energy modeling and optimization, design of distributed systems, and fault-tolerant controls.