标题： 语言建模技术用于分析人类遗传变异的影响 显示英文标题

标题： Language modelling techniques for analysing the impact of human genetic variation

摘要： 解释人类基因组和蛋白质组中变异的影响对于分析疾病风险、预测药物反应和开发个性化健康干预措施至关重要。 由于自然语言和遗传序列结构之间的内在相似性，自然语言处理技术在计算变异效应预测中表现出很大的适用性。 特别是，Transformer的出现推动了该领域的显著进展。 然而，基于Transformer的模型并非没有其局限性，已经开发出许多扩展和替代方法以提高结果并增强计算效率。 本篇综述探讨了过去十年中语言模型在计算变异效应预测中的应用，分析了主要架构，并确定了关键趋势和未来方向。 显示英文摘要

摘要： Interpreting the effects of variants within the human genome and proteome is essential for analysing disease risk, predicting medication response, and developing personalised health interventions. Due to the intrinsic similarities between the structure of natural languages and genetic sequences, natural language processing techniques have demonstrated great applicability in computational variant effect prediction. In particular, the advent of the Transformer has led to significant advancements in the field. However, Transformer-based models are not without their limitations, and a number of extensions and alternatives have been developed to improve results and enhance computational efficiency. This review explores the use of language models for computational variant effect prediction over the past decade, analysing the main architectures, and identifying key trends and future directions.