基于机器学习和深度学习的蛋白质结构预测研究进展
DOI:
https://doi.org/10.52810/FAAI.2024.003Keywords:
蛋白质结构预测, 深度学习, 机器学习, 卷积神经网络, Transformer 模型, 生成式对抗网络Abstract
蛋白质结构预测是生物信息学领域的一个核心问题，对于理解蛋白质功能、药物设计以及疾病研究具有重要意义。传统的蛋白质结构预测方法受限于计算复杂度和预测精度。近年来，随着机器学习和深度学习技术的快速发展，这些先进的方法被广泛应用于蛋白质结构预测中，显著提高了预测的准确性和效率。本文首先介绍了蛋白质结构预测的背景和重要性，然后详细阐述了机器学习和深度学习在蛋白质结构预测中的应用，包括常用的算法、模型架构以及优化策略。最后，本文展望了基于机器学习和深度学习的蛋白质结构预测在未来的发展方向和潜在挑战，为相关领域的研究者提供了有价值的参考。
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