Harnessing Machine Learning in Biotechnology for Advanced Natural Language Processing

Author(s)	Dr. Ranjith Gopalan, Rathi Ramakrishnan
Country	USA
Abstract	This paper discusses machine learning techniques in biotechnology for analyzing protein structure and extracting features based on Natural language processing techniques in Artificial intelligence. Modern biotechnology is providing breakthroughs in products and technologies to address debilitating and rare diseases, thereby contributing to global healing. The convergence of artificial intelligence and biotechnology has emerged as a transformative force in the life sciences, enabling researchers to leverage vast amounts of data and derive meaningful insights. In the context of environmental biotechnology, real-time data processing facilitated by natural language processing is becoming increasingly crucial. The paper explains details about Protein structure is a fascinating and complex topic, essential for understanding how proteins function and different AI techniques for extracting key features associated with specific protein structures. This paper also talks about ethical Implications of AI in Biotechnology Data Privacy and Security Issues and Addressing Bias in Machine Learning Models
Keywords	Artificial intelligence, Natural language Processing, Biotechnology, Protein structure, feature engineering, Deep learning
Field	Computer Applications
Published In	Volume 5, Issue 5, September-October 2023
Published On	2023-10-25
DOI	https://doi.org/10.36948/ijfmr.2023.v05i05.16201
Short DOI	https://doi.org/g8tv9j

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