Cell· Abhinav K. Adduri, Dhruv Gautam, Beatrice Bevilacqua, Mohsen Naghipourfar, Alishba Imran, Rohan Shah, Noam Teyssier, Rishi Verma, Christopher Carpenter, Basak Eraslan, Francis Chalissery, Rajesh Ilango, Vishvak Subramanyam, Chiara Ricci-Tam, Sanjay Nagaraj, Aidan Winters, Mingze Dong, Stefanie Fellinger, Adam Krejci, Tilmann Burckstummer, Sravya Tirukkovular, Jeremy Sullivan, Brian S. Plosky, Nicholas D. Youngblut, Jure Leskovec, Luke A. Gilbert, Silvana Konermann, Patrick D. Hsu, Alexander Dobin, Dave P. Burke, Hani Goodarzi, Yusuf H. Roohani·· 2026-08-31AI 评分18
State 模型跨多样情境预测细胞扰动响应，性能优于基线
Predicting cellular responses to perturbation across diverse contexts with State
AI 导读
在共享嵌入空间中对细胞集合进行训练的 State 模型，在将扰动效应泛化到新情境方面优于基线方法。用于该比较的框架 Cell-Eval 为未来模型提供了全面的基准。
来源：Cell · cell.com