Kumar Prakash, Paul Ranjit Kumar, Roy Himadri Shekhar, Yeasin Md, Singh Deepak, Kumar Raju, Paul Amrit Kumar
ICAR- Indian Agricultural Statistics Research Institute, New Delhi, India.
Methods Mol Biol. 2025;2952:283-295. doi: 10.1007/978-1-0716-4690-8_17.
The synergistic integration of Artificial Intelligence (AI) techniques with bioinformatics, statistics, and biotechnology has ushered in a transformative era in the realms of cell and genetic engineering. This convergence represents a powerful alliance, combining the computational prowess of AI with the wealth of biological information harnessed through bioinformatics and statistical methodologies. The collaborative impact of these disciplines has redefined our approach to understanding, manipulating, and optimizing complex biological systems. By leveraging advanced algorithms, machine learning models, and data analytics, researchers can navigate the intricate molecular landscapes with unprecedented precision. This chapter aims to dissect the multifaceted applications of AI within cell and genetic engineering, shedding light on its role in enhancing precision, efficiency, and innovation. The intricate dance between AI and biological data comes to life, showcasing how algorithms unravel genomic intricacies or predict protein structures. Formulas, grounded in statistical methodologies, underline the quantitative rigor AI brings to these fields. Accompanied by images, this exploration seeks to elucidate the tangible impact of AI on the biological sciences, offering readers a visual journey into the world where computational intelligence meets the intricacies of life at the molecular level.
人工智能（AI）技术与生物信息学、统计学和生物技术的协同整合，在细胞和基因工程领域开启了一个变革性的时代。这种融合代表了一种强大的联盟，将人工智能的计算能力与通过生物信息学和统计方法获取的丰富生物信息结合在一起。这些学科的协同作用重新定义了我们理解、操纵和优化复杂生物系统的方法。通过利用先进的算法、机器学习模型和数据分析，研究人员能够以前所未有的精度探索复杂的分子景观。本章旨在剖析人工智能在细胞和基因工程中的多方面应用，阐明其在提高精度、效率和创新方面的作用。人工智能与生物数据之间错综复杂的互动鲜活呈现，展示了算法如何解开基因组的复杂性或预测蛋白质结构。基于统计方法的公式强调了人工智能带给这些领域的定量严谨性。辅以图像，本探索旨在阐明人工智能对生物科学的切实影响，为读者提供一次视觉之旅，进入计算智能在分子水平上与生命复杂性相遇的世界。
