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ISSN 2063-5346
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The Future is Now: Exploring the Role of AI in Biochemical Structure Analysis

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Proshanta Sarkar
» doi: 10.48047/ecb/2023.12.sa1.503

Abstract

In recent years, artificial intelligence (AI) has made significant progress in various fields, including biochemistry. One area where AI has the potential to revolutionize is in the analysis of biochemical structures. This paper aims to explore the current state of AI in biochemical structure analysis and the potential for future development. First, the paper provides an overview of the different types of biochemical structures and the current methods used for their analysis. The limitations of these methods are discussed, including the time and resource-intensive nature of experimental techniques. The paper then examines the use of AI in biochemical structure analysis. It discusses the different AI techniques used, including machine learning and deep learning, and their applications in tasks such as predicting protein structures and identifying potential drug targets. The potential benefits and challenges of using AI in biochemical structure analysis are also explored. While AI has the potential to greatly improve the speed and accuracy of analysis, there are concerns about the reliability and interpretability of AI-generated results. Finally, the paper concludes by highlighting some of the ongoing research and future directions for the use of AI in biochemical structure analysis. The authors argue that AI has the potential to greatly enhance our understanding of biochemical structures, leading to the development of more effective drugs and treatments. However, it is crucial to ensure that the use of AI is transparent, trustworthy, and ethical.

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