Mr. Subhrangshu Das, Bioinformatics, Best Researcher Award

Subhrangshu Das at CSIR-Indian Institute of Chemical Biology, India

Subhrangshu Das is a highly qualified individual with a diverse academic background and extensive experience in both computer science and structural biology/bioinformatics. He holds a B.Tech. in Computer Science & Engineering, an M.E. in Computer Science & Engineering, and is on the verge of completing his Ph.D. in Structural Biology and Bioinformatics. Throughout his career, Das has demonstrated a keen interest in interdisciplinary research, utilizing his expertise in computer science to contribute to the field of biology.

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Das has an impressive publication record, with several articles published in reputable scientific journals. His research contributions span topics such as Alzheimer’s disease detection, protein-protein interaction interface prediction, and sub-cellular organelle analysis. He has also presented his work at conferences and workshops, further showcasing his expertise and involvement in the scientific community.

Citations: 115 citations by 110 documents.

Documents: 9 documents authored.

h-index: 6. The h-index is a metric that attempts to measure both the productivity and citation impact of the publications of a scientist or scholar. An h-index of 6 means the author has at least 6 papers that have been cited at least 6 times each.

Education:

Das’s educational journey includes a Bachelor of Technology in Computer Science & Engineering, a Master of Engineering in Computer Science & Engineering, and a pending Ph.D. in Structural Biology and Bioinformatics. His academic achievements demonstrate a strong foundation in both computer science and biological sciences, providing him with a unique skill set for interdisciplinary research.

Research Focus:

Das’s research focuses on the intersection of computer science and biology, particularly in the areas of structural biology and bioinformatics. His work involves the development and application of computational algorithms and techniques for analyzing biological data, with specific emphasis on Alzheimer’s disease detection, protein-protein interaction interface prediction, and sub-cellular organelle analysis.

Professional Journey:

Das has a rich professional journey, starting as a Junior Research Fellow and progressing to the role of Senior Research Fellow before becoming a Research Associate at CSIR – Indian Institute of Chemical Biology. Throughout his career, he has been actively involved in research projects, contributing to advancements in structural biology and bioinformatics.

Honors & Awards:

Das has received several honors and awards for his academic and research achievements. Notable accolades include qualifying in GATE and CSIR NET exams, as well as receiving scholarships during his Master’s and Ph.D. studies. These recognitions underscore his dedication and excellence in both academic and research endeavors.

Publications Noted & Contributions:

Das has made significant contributions to the scientific community through his publications in reputable journals. His research on Alzheimer’s disease detection, protein-protein interaction interface prediction, and sub-cellular organelle analysis has advanced our understanding of these complex biological processes. Additionally, his presentations at conferences and workshops have disseminated valuable insights to the scientific community.

Title: CMT2A‐linked mitochondrial hyperfusion‐driving mutant MFN2 perturbs ER‐mitochondrial associations and Ca2+ homeostasis

Authors: R. Das, S. Das, S. Chakrabarti, O. Chakrabarti
Journal: Biology of the Cell
Volume/Issue: 114 (11)
Pages: 309-319
Year: 2022
Citations: 4

Title: Three Dimensional Face Registration by Pose Orientation and Recognition using PCA

Author: S. Das
Year: 2014
Citations: 1
Title: CCADD: An Online Webserver for Alzheimer’s Disease Detection from Brain MRI
Authors: P. Panigrahi, S. Das, S. Chakrabarti
Journal: Computers in Biology and Medicine
Article Number: 108622
Year: 2024

Title: SARS-CoV-2: From Genetic Variability to Vaccine Design

Authors: Nupur Biswas*, Krishna Kumar, Priyanka Mallick, Subhrangshu Das, Izaz Monir Kamal, Sarpita Bose, Anindita Choudhury, Saikat Chakrabarti
Editors: I. Saha, W.H. Chen
Publisher: Springer
Year: 2022

Title: Structural and Drug Screening Analysis of the Non-structural Proteins of Severe Acute Respiratory Syndrome Coronavirus 2 Virus Extracted From Indian Coronavirus Disease 2019

Authors: N. Biswas, K. Kumar, P. Mallick, S. Das, I.M. Kamal, S. Bose, A. Choudhury, …
Journal: Frontiers in Genetics
Article Number: 171

Research Timeline:

Das’s research timeline spans his academic journey from his Bachelor’s degree to his current role as a Ph.D. candidate. Throughout this timeline, he has been actively engaged in research projects, focusing on various aspects of structural biology and bioinformatics. His progression from a Junior Research Fellow to a Research Associate reflects his growth and expertise in the field.

Collaborations and Projects:

Das has been involved in numerous research projects, collaborating with fellow scientists and researchers to address key challenges in structural biology and bioinformatics. His projects have encompassed diverse topics such as Alzheimer’s disease detection, stroke quantification, protein-protein interaction interface prediction, and sub-cellular organelle analysis. Through these collaborations, Das has contributed to interdisciplinary research efforts and fostered innovation in the field.

Assoc Prof Dr. Panjit Musik. Computing science, Best Researcher Award

Associate Professor at Panjit Musik walailak university, Thailand

Assoc. Prof. Dr. Panjit Musik, born on July 4, 1961, is a distinguished academic in the fields of Physics, Computational Science, and Smart Farming. He currently teaches at the School of Science, Walailak University in Thailand. His academic journey and professional accomplishments reflect a commitment to advancing education and research in scientific and technological innovations.

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Dr. Musik has authored numerous research papers published in international and national journals, contributing significantly to the fields of Physics, Computational Science, and Smart Farming. His works are frequently cited, reflecting his influence in these research areas.

Panjit Musik is associated with Walailak University in Tha Sala, Thailand. His academic profile on Scopus shows a modest yet emerging research output, with 4 documents and 5 citations, resulting in an h-index of 1.

Education

Dr. Musik earned his Doctor of Philosophy in Computational Science from Walailak University in 2005. He holds a Master of Science in Teaching Physics from Chiang Mai University, obtained in 1990, and a Bachelor of Education in Physics from Thaksin University, completed in 1983. This strong educational foundation underpins his extensive research and teaching career.

Research Focus

Dr. Musik’s research interests are diverse and interdisciplinary, encompassing Physics Teaching, Real-Time Physics Labs, Computational Modeling and Simulation, and Smart Farming. His work aims to integrate technological advancements with educational practices to enhance learning outcomes and develop innovative solutions for agricultural challenges.

Professional Journey

Dr. Musik’s professional journey began with a focus on physics education and has evolved to include computational modeling and smart farming technologies. He has developed numerous computer-based experimental sets and simulations, contributing to both academic and practical advancements in his fields of expertise.

Honors & Awards

Throughout his career, Dr. Musik has received several accolades for his contributions to science and education. His innovative work in developing experimental sets and integrating computational methods in education has been recognized by academic and professional institutions.

Publications Noted & Contributions

Dr. Musik has published extensively in international journals such as the Turkish Online Journal of Educational Technology and the International Journal on Smart Sensing and Intelligent Systems. His publications address key issues in computational physics, real-time experimental learning, and smart farming technologies, contributing to the academic discourse and practical applications in these areas.

Development of a Computer-Based Simple Pendulum Experiment Set for Teaching and Learning Physics

Authors: Sukmak, W., & Musik, P.
Journal: International Journal on Smart Sensing and Intelligent Systems, 2021, 14(1), pp. 1–8
Citations: 1

Abstract: This article presents the development of a computer-based experiment set designed to enhance the teaching and learning of physics through a simple pendulum experiment. The set aims to provide real-time data acquisition and analysis, making physics concepts more accessible and engaging for students. The development process, implementation, and educational benefits are discussed in detail.

Development of an Automated Water Management System in Orchards in Southern Thailand

Author: Musik, P.
Journal: International Journal on Smart Sensing and Intelligent Systems, 2020, 13(1), pp. 1–7
Citations: 2

Abstract: Dr. Musik explores the design and implementation of an automated water management system tailored for orchards in southern Thailand. This system leverages smart sensing technologies to optimize water usage, ensuring efficient irrigation and enhancing crop yields. The article details the system’s components, operational mechanisms, and the positive impact on orchard management.

Development of Computer-Based Experiment Set on Simple Harmonic Motion of Mass on Springs

Author: Musik, P.
Journal: Turkish Online Journal of Educational Technology, 2017, 16(4), pp. 1–11
Citations: 1

Abstract: This study describes the creation of an experimental set for investigating the simple harmonic motion of a mass on a spring. The set integrates computer-based tools to facilitate real-time data collection and visualization, aiming to improve students’ understanding of oscillatory motion through interactive and hands-on learning experiences.

Large-Scale Simulation Using Parallel Computing Toolkit and Server Message Block

Authors: Musik, P., & Jaroensutasinee, K.
Journal: WSEAS Transactions on Mathematics, 2007, 6(2), pp. 369–372
Citations: 1

Abstract: This paper discusses a large-scale simulation approach using a parallel computing toolkit and server message block. The simulation targets complex mathematical models, enhancing computational efficiency and accuracy. The authors highlight the methodology, computational framework, and potential applications in scientific research.

These articles reflect Dr. Panjit Musik’s extensive work in developing innovative educational tools and applying computational methods to solve practical problems in agriculture and physics education. His research contributes significantly to enhancing teaching methodologies and improving resource management in various domains.

Research Timeline

Dr. Musik’s research timeline spans over three decades, beginning with his master’s research in 1990 on computer control of humidity in experimental greenhouses. His doctoral research in 2005 focused on large-scale water flow simulation using Mathematica. In the years following, he has conducted numerous studies on integrating remote sensing data, developing computer-based experiments, and smart farming solutions.

Collaborations and Projects

Dr. Musik has collaborated with various researchers and institutions on projects aimed at developing innovative educational tools and smart farming technologies. His projects include the development of watershed and hydrologic process modeling for flood forecasting, automated water management systems in orchards, and GIS applications for agricultural water management.

Contributions to the Field

Dr. Musik’s contributions to the field include the development of computer-based experimental sets for physics education, large-scale simulations for environmental modeling, and smart farming technologies. His work has provided valuable insights and practical tools for educators, researchers, and farmers, advancing both academic knowledge and real-world applications.

Subhrangshu Das | Bioinformatics | Best Researcher Award