Computational models
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Advanced Computational Models for Predicting Molecular Interactions
Abstract: Understanding molecular interactions is essential for a number of disciplines, including biochemistry, materials science, and medication development. Traditional experimental methods, while accurate, are often time-consuming and expensive. Advanced computational models have emerged as powerful tools to predict molecular interactions efficiently. In order to predict the behavior and interactions of molecules at the atomic and subatomic levels, this paper reviews the most recent developments in computational techniques, such as machine learning …
Published in International Journal of Advance in Molecular Engineering · Vol. 2, Issue 1, 2024 · pp. 8–13 Read article
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Advancements in Molecular Engineering: Innovations at the Nexus of Chemistry and Technology
Abstract: Molecular engineering, a frontier of chemistry, merges precision and innovation to design and assemble molecular structures with unprecedented control. This abstract explores recent advances, highlighting key breakthroughs and their transformative impacts. Starting with its roots in chemical synthesis and materials science, it traces the evolution towards rational design driven by computational tools and advanced characterization techniques, enabling tailored molecular architectures. A focal point is programmable molecules, where DNA nanotechnology principles …
Published in International Journal of Advance in Molecular Engineering · Vol. 1, Issue 2, 2023 · pp. 37–43 Read article
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Exploring Practical Applications of Artificial Neural Networks: A Review
Abstract: Computational models called artificial neural networks (ANNs) are modeled after the structure of the human brain. These models are designed to process information and learn from data. Artificial neural networks, or ANNs, are composed of interconnected artificial neurons layered to resemble the brain's neural network.. Through training, ANNs adjust the connections between neurons based on labeled data, enabling them to recognize patterns and perform specific tasks. Despite their efficacy in …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 11, Issue 2, 2024 · pp. 1–11 Read article