标题： 基于系统发育的基因组语言建模 显示英文标题

标题： A Phylogenetic Approach to Genomic Language Modeling

摘要： 基因组语言模型（gLMs）在识别哺乳动物基因组中进化约束的元件方面表现出的成果大多较为有限。 为解决这一问题，我们引入了一种新的训练gLMs的框架，该框架通过多物种全基因组比对显式地对系统发育树上的核苷酸进化进行建模。 我们的方法在训练过程中将比对整合到损失函数中，但进行预测时不需依赖比对，从而提高了模型的适用性。 我们将这个框架应用于训练PhyloGPN，该模型擅长仅从单个序列中预测功能破坏性变异，并表现出强大的迁移学习能力。 显示英文摘要

摘要： Genomic language models (gLMs) have shown mostly modest success in identifying evolutionarily constrained elements in mammalian genomes. To address this issue, we introduce a novel framework for training gLMs that explicitly models nucleotide evolution on phylogenetic trees using multispecies whole-genome alignments. Our approach integrates an alignment into the loss function during training but does not require it for making predictions, thereby enhancing the model's applicability. We applied this framework to train PhyloGPN, a model that excels at predicting functionally disruptive variants from a single sequence alone and demonstrates strong transfer learning capabilities.