English(EN) BioM-JEPA: joint-embedding prediction of graph-connected gene blocks in single cells

BioM-JEPA模型推进单细胞基因块分析

作者 PulseAugur 编辑部 · [2 个来源] · 2026-08-06 11:58

研究人员推出BioM-JEPA，一种用于分析单细胞转录组的新型联合嵌入预测架构。与重建单个基因的先前模型不同，BioM-JEPA预测图连接基因块的聚合表示。这种方法利用学生-教师网络结构，在保留生物信息和在比较任务上实现更低错误率方面表现出优越性能。 AI

影响该模型可以改进复杂生物数据的分析，可能加速遗传学和医学领域的发现。

排序理由该集群描述了一篇关于用于生物数据分析的新型机器学习模型的科学论文。

AI 生成摘要 · Google Gemini · 来自 2 个来源。我们如何撰写摘要 →

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arXiv cs.LG TIER_1 English(EN) · Yuhao Wang, Zelin Zang, Yuxuan Liu, Zhen Lei, Stan Z. Li · 2026-08-07 04:00

BioM-JEPA：单细胞中图连接基因块的联合嵌入预测

arXiv:2608.05928v1 Announce Type: new Abstract: Single-cell transcriptomes are sparse observations of coordinated biological programmes, yet most self-supervised models learn by reconstructing individual genes. Here we present BioM-JEPA, a joint-embedding predictive architecture …
Hugging Face Daily Papers TIER_1 English(EN) · 2026-08-06 11:58

BioM-JEPA：单细胞中图连接基因块的联合嵌入预测

Single-cell transcriptomes are sparse observations of coordinated biological programmes, yet most self-supervised models learn by reconstructing individual genes. Here we present BioM-JEPA, a joint-embedding predictive architecture that instead predicts aggregate representations …