Posted on 10/07/202410/07/2024 by sciencefatherLeave a Comment on MohammadSadeq Mottaqi | Machine Learning | Best Researcher Award 83 / 100 Powered by Rank Math SEO MohammadSadeq Mottaqi | Machine Learning | Best Researcher Award Dr. MohammadSadeq Mottaqi, City University of New York, United States. Dr. MohammadSadeq Mottaqi is a Ph.D. candidate in Biochemistry at the City University of New York, with a background in Biotechnology from the University of Tehran. Proficient in Python and R, Mohammad excels in bioinformatics tools like PyMol and Gromacs. His research spans machine learning-based drug action prediction, molecular dynamics simulations, and protein-ligand interactions. He has published on topics such as SARS-CoV-2 infection responses and cyanobacterial genera identification. Mohammad’s technical prowess extends to data analysis, visualization, and high-performance computing, reflecting his commitment to advancing biotechnological and computational research. Publication Profile Scopus orcid Education Ph.D. in Biochemistry City University of New York, New York, NY Aug 2022 – Present Bachelor of Science in Biotechnology University of Tehran, Tehran, Iran Sep 2017 – March 2022 Experience Graduate Assistant City University of New York, New York, NY Aug 2022 – Present Assisting in bioinformatics and computational biochemistry research. Research Experience Conducted molecular dynamics simulations of mutated HER2 proteins. Investigated protein-ligand interactions using Python and PyMOL. Developed machine learning models for predicting drug actions. Professional Development Mr.Mohammad Sadeq Mottaqi is currently immersed in his Ph.D. journey in Biochemistry at the City University of New York, focusing on computational biochemistry. His research expertise includes pioneering machine learning approaches for predicting drug actions and analyzing transcriptomics data to advance personalized medicine. Mohammad’s impactful contributions extend to molecular dynamics simulations of protein interactions and investigating the molecular mechanisms of SARS-CoV-2 mutations. With a foundation in biotechnology from the University of Tehran, he blends technical skills in Python, R, and bioinformatics tools like Gromacs and PyMol. Mohammad is dedicated to pushing the boundaries of bioinformatics, bridging theoretical insights with practical applications in healthcare and environmental management. Research Focus Mr. MohammadSadeq Mottaqi is a biochemist and computational scientist specializing in bioinformatics and machine learning applications in drug discovery and molecular biology. His research includes predictive modeling for drug actions, molecular dynamics simulations, and protein-ligand interactions. Mohammad has contributed significantly to understanding SARS-CoV-2 through machine learning approaches and automated identification of toxigenic cyanobacterial genera for water quality control. His work, cited extensively, showcases his expertise in integrating computational tools and biotechnological research, making impactful advancements in these fields. Publications Automated identification of toxigenic cyanobacterial genera for water quality control purposes, Journal of Environmental Management, 2024 Contribution of machine learning approaches in response to SARS-CoV-2 infection, Informatics in Medicine Unlocked, 2021 Mutations in SARS-CoV-2; Consequences in structure, function, and pathogenicity of the virus, Microbial Pathogenesis, 2021 MohammadSadeq Mottaqi | Machine Learning | Best Researcher Award