Keystone: Single Cell Biology: Expanding Potential Across Diseases
Keystone Symposia · Banff, Canada (to Feb 18) · 2027-02-15
Keystone 2027单细胞会议。
标签：扰动
共 21 条，按时间倒序。
Engineered regulatory states resolve context-dependent genetics in macular degeneration
Metzner E, Guruvayurappan K, Southard KM, Ardy RC, Dey KK, Norman TM. · bioRxiv · 2026-10-12
Norman/Dey 实验室（MSKCC）：在 RPE-1 中对 119 个 TF 做 CRISPRa Multiome Perturb-seq、对 1,225 个 TF 对做双向导 Perturb-seq；染色质预激活可预测新兴状态；Mosaic（Transformer）预测 TF 对相互作用残差（r=0.484），并提名经实验验证的三 TF 组合。
An operational perturbation proteomics-based virtual cell model.
Sun R et al. · Nature · 2026-09-09
Nature 2026：基于扰动蛋白质组的可操作虚拟细胞模型。
Predicting cellular responses to perturbation across diverse contexts with State.
Adduri AK et al. · Cell · 2026-08-31
Arc的State模型：跨70种细胞情境预测扰动反应（Cell 2026）。
PerturbLDM: conditional latent diffusion for modelling single-cell perturbation responses
Yu et al. · bioRxiv · 2026-08-12
PerturbLDM：在Tahoe-100M上预训练的条件潜扩散模型，生成药物/剂量/细胞系扰动的单细胞响应。
UniPert-G2CP bridges genetic and chemical screens from molecular representation to phenotype modeling
Li et al. · Cell · 2026-08
UniPert-G2CP：统一基因/化学扰动表征，并把CRISPR筛查迁移到药物表型预测。
TxPert: using multiple knowledge graphs for prediction of transcriptomic perturbation effects.
Wenkel F et al. · Nature biotechnology · 2026-05-01
TxPert：多知识图谱预测转录组扰动效应。
Harnessing AI to Build Virtual Cells (VCHarness)
Cheng et al. · bioRxiv · 2026-04-14
VCHarness：用自主AI编程智能体搜索并迭代扰动响应架构，加速虚拟细胞组件构建。
X-Cell: Scaling Causal Perturbation Prediction Across Diverse Cellular Contexts via Diffusion Language Models
Wang C et al. · bioRxiv · 2026-03-20
Xaira的X-Cell：49亿参数扩散模型，显示扰动预测的缩放规律。
AetherCell: A generative engine for virtual cell perturbation and in vivo drug discovery
Li et al. · bioRxiv · 2026-03-16
AetherCell统一临床RNA-seq与扰动实验流形，做生成式响应预测并支持体内药物重定位。
Towards building a World Model to simulate perturbation-induced cellular dynamics by AlphaCell
Chuai et al. · bioRxiv · 2026-03-05
AlphaCell：全基因组虚拟细胞世界模型，用最优传输条件流匹配做跨语境扰动动力学。
DELPHAI, AI Agent for Predicting Drug Response and Resistance
Peng et al. · preprint · 2025-09-17
DELPHAI：GBM类器官+TMZ的单细胞扰动预测与LLM机制解读；最优传输+PCA优于基线。
Predicting cellular responses to perturbation across diverse contexts with State
Adduri AK et al. · bioRxiv · 2025-06-27
State模型预印本。
A perturbation proteomics-based foundation model for virtual cell construction
Sun R, Qian L, Li Y, Cheng H, Xue Z, Zhang X, Tan L, Zhan Y, Hu W, Xiao Q, Liu Z, Zhang G, Weinan E, Zhou P, Wen H, Zhu Y, Guo T. · bioRxiv · 2025-02-10
上述扰动蛋白组虚拟细胞模型预印本。
PertEval-scFM: Benchmarking Single-Cell Foundation Models for Perturbation Effect Prediction
Wenteler A, Occhetta M, Branson N, Curean V, Huebner M, Dee W, Connell W, Chung SP, Hawkins-Hooker A, Ektefaie Y, Valdez Córdova CM, Gallagher-Syed A. · bioRxiv · 2024-10-03
PertEval-scFM：扰动预测基准。
scGPT: toward building a foundation model for single-cell multi-omics using generative AI.
Cui H, Wang C, Maan H, Pang K, Luo F, Duan N, Wang B. · Nature methods · 2024-02-26
scGPT：基于3300万细胞的生成式单细胞基础模型（王波团队）。
Disentanglement of single-cell data with biolord.
Piran Z, Cohen N, Hoshen Y, Nitzan M. · Nature biotechnology · 2024-01-15
biolord：解耦表示进行反事实细胞预测。
Learning single-cell perturbation responses using neural optimal transport.
Bunne C, Stark SG, Gut G, Del Castillo JS, Levesque M, Lehmann KV, Pelkmans L, Krause A, Rätsch G. · Nature methods · 2023-09-28
CellOT：神经最优传输预测扰动反应。
Predicting transcriptional outcomes of novel multigene perturbations with GEARS.
Roohani Y, Huang K, Leskovec J. · Nature biotechnology · 2023-08-17
GEARS：知识图谱图神经网络预测多基因扰动。
Predicting cellular responses to complex perturbations in high-throughput screens.
Lotfollahi M et al. · Molecular systems biology · 2023-05-08
CPA：组合扰动自编码器，预测药物/剂量/组合反应。
scGen predicts single-cell perturbation responses.
Lotfollahi M, Wolf FA, Theis FJ. · Nature methods · 2019-07-29
scGen：早期基于VAE的单细胞扰动预测。