Keystone: AI and Gene Regulation Across Scales
Keystone Symposia · Breckenridge, CO (to Oct 7) · 2027-10-04
Keystone AI与基因调控会议（日期待复核）。
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AACR Annual Meeting 2027
AACR · Orlando, FL (to Apr 7) · 2027-04-02
AACR 2027：4月2-7日奥兰多。
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。
NeurIPS 2026 Workshop: Foundation Models for the Brain and Body
NeurIPS · NeurIPS 2026, Sydney · 2026-12-11
NeurIPS 2026脑与身体基础模型研讨会。
AgenticLS @ NeurIPS 2026 — Agentic AI for Biological Discovery
NeurIPS · NeurIPS 2026, Sydney · 2026-12-11
NeurIPS 2026生物发现智能体研讨会。
SIMBIOCHEM II · NeurIPS 2026 Workshop on ML for Simulation
NeurIPS · NeurIPS 2026, Sydney · 2026-12-11
NeurIPS 2026生物化学模拟研讨会。
SNO 2026 31st Annual Meeting
Society for Neuro-Oncology · Philadelphia, PA (to Nov 15) · 2026-11-12
SNO 2026：11月12-15日费城；2027年11月18-21日凤凰城。
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。
A State-Resolved Single-Cell and Spatial Atlas Reveals IDH-Associated Differences in Malignant and Immune Architecture in Diffuse Glioma.
Zaman A et al. · MedComm · 2026-10-04
IDH相关胶质瘤状态分辨图谱。
ISP 3 Platform powered by Geneformer: Framework for Cross-Species, Sequential, and Multi-Gene In Silico Perturbation Screens with Application to iPS Cell State Transitions
Sanaki Y, Shigenobu S, Niwa R. · bioRxiv · 2026-09-24
ISP3平台：基于Geneformer的多基因序贯模拟扰动。
EANO 2026 (21st meeting)
European Association of Neuro-Oncology · Rome, Italy (to Sep 27) · 2026-09-24
EANO 2026：9月24-27日罗马（已结束）。
Beyond the drug-centric view: Advancing AI virtual cell platforms for environmental perturbation modelling.
Ukaegbu D, Curean V, Bender A, Maertens A. · ALTEX · 2026-09-17
观点：虚拟细胞用于环境暴露/毒理扰动建模。
Spatial and single-cell dissection of medulloblastoma identifies developmental hierarchies and a prognostic PPIA-BSG tumor-immune axis.
Chen M, Duan B, Zhang J, Daniels C, Hu C, Yuan J, Guo J, Taylor MD, Shi X, Zhang L, Li D, Sun T. · Journal of translational medicine · 2026-09-15
髓母细胞瘤空间与单细胞层级（2026）。
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。
Tahoe-100M: Mapping drug-induced molecular phenotypes at single-cell resolution.
Zhang J et al. · Cell · 2026-09-01
Tahoe-100M正式发表于Cell 2026。
scBaseCount: An AI agent-curated, standardized, auto-updated single-cell data repository.
Youngblut ND et al. · Cell · 2026-09-01
scBaseCount：AI代理自动整理的单细胞数据库（Arc）。
A world model of the virtual cell
Xing et al. · Cell · 2026-09
Cell正式版VCWM：持久多模态虚拟细胞世界模型，区别于任务型预测基础模型。
引用于： AI 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）。
引用于： AI 虚拟细胞模型 · 胶质母细胞瘤扰动数据：放疗、药物与 CRISPR · 虚拟细胞的验证：基准、基线与批评
Virtual Cell Challenge 2026: Benchmarking zero-shot generalization across cellular contexts.
Arc Virtual Cell Initiative Team, Goodarzi H. · Cell · 2026-08-26
2026挑战赛论文：跨细胞情境零样本泛化基准。
引用于： AI 虚拟细胞模型 · 虚拟细胞的验证：基准、基线与批评
Virtual Cell Challenge 2026 (zero-shot, 6 unseen cell lines)
Arc Institute · virtualcellchallenge.org · 2026-08-20
2026挑战赛：8月20日起验证；10月22日发布终测集；11月5日23:59 UTC截止；11月中下旬公布（Arc官网确认）。
AIDO Cell: a general-purpose simulator for cell biology
GenBio AI · GenBio web · 2026-08-18
GenBio的有状态多模态细胞模拟器。
Biological domain shift and statistical nesting concerns in generative AI-based spatial tumor growth prediction for pediatric diffuse midline glioma.
Li W, Sun X, Pei S. · BMC medicine · 2026-08-12
对上述DMG生成模型的方法学批评。
引用于： 虚拟细胞的验证：基准、基线与批评
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。
Assessing scale and predictive diversity in models for single-cell transcriptomics based on Geneformer.
Chen J, Schmidt F, Henao R. · PLoS computational biology · 2026-07-30
评估Geneformer类模型的规模效应。
Core2Edge: a human glioblastoma organoid-brain slice model capturing infiltration and transcriptional heterogeneity from core to single-cell dispersion.
Melhem A et al. · Nature protocols · 2026-07-28
Core2Edge：GBM类器官-脑片浸润模型。
引用于： 胶质母细胞瘤单细胞与空间数据集
An Empirical Comparison of Virtual Cell Models: Perturbation Prediction, Representation, and the Baseline Gap
Denvis O. · Research Square · 2026-07-22
虚拟细胞模型实证比较：与基线差距依旧。
引用于： 虚拟细胞的验证：基准、基线与批评
Systematic evaluation of single-cell foundation model interpretability: attention-derived edge scores add no incremental value over gene-level features for perturbation-target prediction.
Kendiukhov I. · BMC genomics · 2026-07-22
单细胞基础模型注意力边得分未增加调控网络信息。
引用于： 虚拟细胞的验证：基准、基线与批评
Causal Models Need Causal Data - Xaira's X-Cell (podcast)
Latent Space · Latent Space podcast · 2026-07-21
播客：因果数据与扩散模型。
ISMB 2026
ISCB · Washington, DC (to Jul 16) · 2026-07-12
ISMB 2026：7月12-16日华盛顿。
ICML 2026 3rd Workshop on Multi-modal FMs & LLMs for Life Sciences
ICML · ICML 2026, COEX Seoul · 2026-07-11
ICML 2026生命科学多模态基础模型研讨会。
A World Model of the Virtual Cell (ICML 2026)
ICML 2026 · ICML 2026 · 2026-07
提出“虚拟细胞世界模型”的操作性定义。
Lessons from Ron Alfa (Noetik) on AI-native precision oncology
Pear Healthcare Playbook · Substack · 2026-06-30
Noetik CEO访谈。
Single-cell and spatial transcriptomes reveal oligodendrocyte remodeling fatty acid metabolism microenvironment of lung cancer brain metastases.
Yang Y, Gao Y, Qi Z, Li S, Wang Z, Li D, Chen L, Zhou C, Feng M, Chen X, Hao B, Wu X, Li L, Cao Y. · Journal of translational medicine · 2026-06-16
脑转移中少突胶质细胞脂肪酸代谢重塑。
Automated and personalized glioblastoma tumor organoid drug screening platform exposes sensitivity to proteasome and HDAC inhibitors.
Jungwirth G et al. · NPJ precision oncology · 2026-06-16
自动化个体化GBM类器官药筛平台。
Cellfm-datasets: A Unified Data Infrastructure for Single-Cell and Spatial Transcriptomics Foundation Model Pretraining
Zhang L, Pang J, Yan J, Tang W, Deng Y, He Y. · bioRxiv · 2026-06-14
CellFM-datasets：统一单细胞与空间数据基础设施。
RECOMB 2026
RECOMB · Thessaloniki, Greece (to May 29) · 2026-05-26
RECOMB 2026；2027据称在多伦多（日期未确认）。
Generative AI for spatial tumor growth on MRI: a proof-of-principle study in pediatric diffuse midline glioma.
Laslo D et al. · BMC medicine · 2026-05-18
生成式AI预测儿童DMG的MRI空间生长。
引用于： 虚拟细胞的验证：基准、基线与批评
TumorTwin: a Python framework for patient-specific digital twins in oncology
Kapteyn et al. · BMC Med Inform Decis Mak · 2026-05-11
开源模块化Python肿瘤数字孪生框架；演示高级别胶质瘤生长与放疗反应。
引用于： 胶质母细胞瘤的治疗诱导可塑性
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。
LMRL Workshop @ ICLR 2026 (virtual cells)
ICLR · ICLR 2026, Rio de Janeiro · 2026-04-27
ICLR 2026 LMRL虚拟细胞研讨会。
Discovery of candidate therapeutic targets with Geneformer.
Zhang Y, Venkatesh MS, Theodoris CV. · Nature protocols · 2026-04-23
Nature Protocols：用Geneformer进行靶点发现的流程。
A Proteome-Calibrated Mechanistic Digital Twin of the Glioblastoma Astrocyte Derived from Patient Multi-Omic Data
Mayfield JD. · bioRxiv · 2026-04-23
蛋白质组校准的GBM星形细胞机制性数字孪生（预印本）。
引用于： AI 虚拟细胞模型
A longitudinal single-cell and spatial multiomic atlas of pediatric high-grade glioma.
Sussman JH et al. · Cell reports. Medicine · 2026-04-23
儿童高级别胶质瘤纵向单细胞/空间图谱。
引用于： 胶质母细胞瘤的治疗诱导可塑性
Signal, Bounds, and Baselines: Principles for Evaluating Virtual Cell Perturbation Models
Vollenweider M, Bühlmann P. · bioRxiv · 2026-04-22
虚拟细胞扰动模型评估原则：信号、上界与基线。
引用于： 虚拟细胞的验证：基准、基线与批评
Training transformers to solve cancer trial failure — Ron Alfa & Daniel Bear, Noetik
Latent Space · Latent Space podcast · 2026-04-20
Noetik肿瘤空间虚拟细胞模型TARIO-2与GSK合作。
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。
Scaling Bio 007: Xaira's Bo Wang and Ci Chu on building the virtual cell
Decoding Bio · Substack · 2026-03-30
王波、Ci Chu访谈：X-Cell与泛化局限。
Xaira's first virtual cell model is largest to-date
GEN · GEN · 2026-03-25
GEN报道X-Cell，并含Noetik观点。
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。
引用于： AI 虚拟细胞模型 · 虚拟细胞的验证：基准、基线与批评
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。
Current landscape of single-cell genomics in meningioma.
Ellenbogen Y, Landry AP, Yefet LS, Ajisebutu A, Gui C, Persaud P, Kaloti R, Nassiri F. · Neuro-oncology advances · 2026-02-27
综述：脑膜瘤单细胞基因组学现状。
Foundation Model Based on Routine Magnetic Resonance Imaging for Brain Tumor Molecular Profiling and Progression Prediction.
Li J, Liu R, Xing Y, Gao X, Yin Q, Su Q. · JCO precision oncology · 2026-02-20
基于常规MRI的脑肿瘤分子分型基础模型。
Scalable probe-based single-cell transcriptional profiling for virtual cell perturbation mapping and synthetic biology phenotyping
Swinderman JT et al. · bioRxiv · 2026-02-05
探针法可扩展单细胞测序用于虚拟细胞扰动图谱。
CellFluxV2 : An Image Generative Foundation Model for Virtual Cell Modeling
Zhang Y, Su Y, Wefers Z, Su S, Li H, Li T, Wang C, Burgess J, Lozano A, Zhou L, Ding D, Nirschl J, Lundberg E, Yeung-Levy S. · bioRxiv · 2026-01-20
CellFluxV2：面向虚拟细胞的图像生成基础模型。
Anatomically aware simulation of patient-specific glioblastoma xenografts
Malik et al. · PLoS Comput Biol · 2026-01-20
基于小鼠脑解剖的患者特异性GBM异种移植生长/侵袭模型；ABC拟合；通过扰动参数模拟治疗。
Drug and single-cell gene expression integration identifies sensitive and resistant glioblastoma cell populations
Suter et al. · Nature Communications · 2026-01-07
scFOCAL/ISOSCELES：把GBM细胞状态接到L1000药签，预测状态敏感度并验证OLIG2抑制剂+Depatux-M。
引用于： 胶质母细胞瘤间充质样（MES 样）细胞状态 · 神经前体样（NPC 样）与少突前体样（OPC 样）胶质瘤细胞状态 · AI 虚拟细胞模型 · 胶质母细胞瘤扰动数据：放疗、药物与 CRISPR · 胶质母细胞瘤的治疗诱导可塑性
scPRINT-2: Towards the next-generation of cell foundation models and benchmarks
Kalfon J, Peyré G, Cantini L. · bioRxiv · 2025-12-15
scPRINT-2：新一代细胞基础模型与基准。
A single-cell atlas of RNA alternative splicing in the glioma-immune ecosystem.
Song X, Tiek D, Lu M, Yu X, Wu R, Walker M, He Q, Sisbarro D, Hu B, Cheng SY. · Genome biology · 2025-12-12
胶质瘤-免疫生态可变剪接单细胞图谱。
AI-driven virtual cell models in preclinical research: technical pathways, validation mechanisms, and clinical translation potential.
Ma C, Zhang H, Rao Y, Jiang X, Liu B, Sun Z, Song Z, Gao Y, Cui Y, Liu X, Li Z. · NPJ digital medicine · 2025-12-11
综述：AI虚拟细胞在临床前研究中的技术路径与验证机制。
Novae: a graph-based foundation model for spatial transcriptomics data.
Blampey Q, Benkirane H, Bercovici N, Mulder K, Gessain G, Ginhoux F, André F, Cournède PH. · Nature methods · 2025-12-10
Novae：基于图的空间转录组基础模型。
NeurIPS 2025: Altos Labs wins Generalist Prize at Arc's Virtual Cell Challenge
GEN (Fay Lin) · GEN · 2025-12-08
GEN报道挑战赛结果。
Virtual Cell Challenge 2025 Wrap-Up: Winners and Reflections
Arc Institute · Arc news · 2025-12-06
2025挑战赛结果：百图生科第一、四川大学第二；指标可被“刷分”的教训。
A foundation model for brain tumor MRI analysis: WHO grading and subtype classification.
Li J, Liu R, Xing Y, Gao X, Yin Q, Su Q. · Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology · 2025-11-19
脑肿瘤MRI基础模型：WHO分级与亚型。
STPath: a generative foundation model for integrating spatial transcriptomics and whole-slide images.
Huang T, Liu T, Babadi M, Ying R, Jin W. · NPJ digital medicine · 2025-11-14
STPath：整合全切片图像与空间转录组的生成模型。
BRD2 bromodomain-mediated regulation of cell state plasticity modulates therapy response in glioblastoma.
Vadla R et al. · Neuro-oncology · 2025-11-01
BRD2调控GBM状态可塑性与治疗反应。
引用于： 胶质母细胞瘤间充质样（MES 样）细胞状态 · 胶质母细胞瘤扰动数据：放疗、药物与 CRISPR · 胶质母细胞瘤的治疗诱导可塑性
Nicheformer: a foundation model for single-cell and spatial omics.
Tejada-Lapuerta A, Schaar AC, Gutgesell R, Palla G, Halle L, Minaeva M, Vornholz L, Dony L, Drummer F, Richter T, Bahrami M, Theis FJ. · Nature methods · 2025-10-30
Nicheformer：单细胞+空间组学基础模型（Theis团队）。
Charting the single-cell and spatial landscape of IDH-wild-type glioblastoma with GBmap.
Ruiz-Moreno C et al. · Neuro-oncology · 2025-10-01
GBmap：IDH野生型GBM单细胞与空间参考图谱。
引用于： 胶质母细胞瘤间充质样（MES 样）细胞状态 · 神经前体样（NPC 样）与少突前体样（OPC 样）胶质瘤细胞状态 · 胶质母细胞瘤单细胞与空间数据集 · Neftel 式 GBM 状态判定能否跨平台复现？GlioState 再分析（初稿）
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。
Systema: a framework for evaluating genetic perturbation response prediction beyond systematic variation.
Viñas Torné R, Wiatrak M, Piran Z, Fan S, Jiang L, Teichmann SA, Nitzan M, Brbić M. · Nature biotechnology · 2025-08-25
Systema：剔除系统性变异后评估扰动预测。
引用于： AI 虚拟细胞模型 · 虚拟细胞的验证：基准、基线与批评
rBio: reasoning model trained on virtual cell simulations
Chan Zuckerberg Initiative · CZI blog · 2025-08-20
rBio：以TranscriptFormer为软验证器训练的生物推理大模型。
Multiscale mathematical model-informed reinforcement learning optimizes combination treatment scheduling in glioblastoma evolution.
Liu Z, Zhang J, Hong L, Nie Q, Sun X. · Science advances · 2025-08-08
多尺度机制模型+强化学习优化胶质瘤联合治疗时序。
引用于： 胶质母细胞瘤的治疗诱导可塑性
Deep-learning-based gene perturbation effect prediction does not yet outperform simple linear baselines.
Ahlmann-Eltze C, Huber W, Anders S. · Nature methods · 2025-08-04
Ahlmann-Eltze等：深度模型未超越简单线性基线。
引用于： 胶质母细胞瘤间充质样（MES 样）细胞状态 · AI 虚拟细胞模型 · 胶质母细胞瘤扰动数据：放疗、药物与 CRISPR · 胶质母细胞瘤的治疗诱导可塑性 · 虚拟细胞的验证：基准、基线与批评 · Neftel 式 GBM 状态判定能否跨平台复现？GlioState 再分析（初稿）
Human interpretable grammar encodes multicellular systems biology models to democratize virtual cell laboratories.
Johnson JAI et al. · Cell · 2025-07-26
可解释“语法”驱动的多细胞主体模型，降低虚拟细胞实验室门槛（含肿瘤示例）。
Can AI build a virtual cell? Scientists race to model life's smallest unit.
Callaway E. · Nature · 2025-07-01
Nature新闻特稿：科学家竞相构建AI虚拟细胞。
Single-cell analysis reveals a longitudinal trajectory of meningioma evolution and heterogeneity.
Lee JY, Lee EJ, Seo BY, Kim J, Song Y, Lee D, Moon N, Koo H, Park CK, Kim MS, Park SI, Nam DH, Kong DS, Sa JK. · Nature communications · 2025-07-01
脑膜瘤纵向单细胞演化轨迹。
Multimodal Benchmarking of Foundation Model Representations for Cellular Perturbation Response Prediction
Hasanaj E, Cole E, Mohammadi S, Addagudi S, Zhang X, Song L, Xing EP. · bioRxiv · 2025-06-28
多模态基础模型表示的扰动预测基准。
Predicting cellular responses to perturbation across diverse contexts with State
Adduri AK et al. · bioRxiv · 2025-06-27
State模型预印本。
Arc Institute's first virtual cell model: State
Arc Institute · Arc news · 2025-06-23
Arc发布State模型新闻。
X-Atlas/Orion: Genome-wide Perturb-seq Datasets via a Scalable Fix-Cryopreserve Platform for Training Dose-Dependent Biological Foundation Models
Huang AC et al. · bioRxiv · 2025-06-16
X-Atlas/Orion：Xaira全基因组Perturb-seq数据集。
Bioptimus: multimodal biology foundation model (NVIDIA compute)
Bioptimus · Bioptimus news · 2025-06-11
法国Bioptimus多尺度生物基础模型。
Virtual Cell Challenge: Toward a Turing test for the virtual cell.
Roohani YH et al. · Cell · 2025-06-01
Arc研究所发起虚拟细胞挑战赛，作为虚拟细胞的“图灵测试”。
引用于： AI 虚拟细胞模型 · 虚拟细胞的验证：基准、基线与批评
A visual-omics foundation model to bridge histopathology with spatial transcriptomics.
Chen W et al. · Nature methods · 2025-05-29
病理图像与空间转录组桥接的视觉-组学基础模型。
Interactions between cancer cells and immune cells drive transitions to mesenchymal-like states in glioblastoma.
Hara T et al. · Cancer cell · 2025-05-27
免疫细胞驱动GBM向间充质样状态转变。
Virtual Cells: Predict, Explain, Discover (arXiv 2505.14613)
Recursion / Valence Labs · arXiv · 2025-05-20
Recursion观点：虚拟细胞应能预测、解释、发现。
Spatial epigenomic niches underlie glioblastoma cell state plasticity
Kint S et al. · bioRxiv · 2025-05-14
空间表观生态位决定GBM状态可塑性。
引用于： 胶质母细胞瘤单细胞与空间数据集 · 胶质母细胞瘤的治疗诱导可塑性
A Cross-Species Generative Cell Atlas Across 1.5 Billion Years of Evolution: The TranscriptFormer Single-cell Model
Pearce JD, Simmonds SE, Mahmoudabadi G, Krishnan L, Palla G, Istrate A, Tarashansky A, Nelson B, Valenzuela O, Li D, Quake SR, Karaletsos T. · bioRxiv · 2025-04-29
CZI的TranscriptFormer：跨12物种、1.12亿细胞的生成式模型。
TranscriptFormer model overview (blog)
Chan Zuckerberg Initiative · CZI blog · 2025-04-29
CZI介绍TranscriptFormer的博客。
Benchmarking foundation cell models for post-perturbation RNA-seq prediction.
Csendes G, Sanz G, Szalay KZ, Szalai B. · BMC genomics · 2025-04-23
Csendes等：基础模型扰动预测不如简单基线。
引用于： 胶质母细胞瘤间充质样（MES 样）细胞状态 · AI 虚拟细胞模型 · 虚拟细胞的验证：基准、基线与批评 · Neftel 式 GBM 状态判定能否跨平台复现？GlioState 再分析（初稿）
Zero-shot evaluation reveals limitations of single-cell foundation models.
Kedzierska KZ, Crawford L, Amini AP, Lu AX. · Genome biology · 2025-04-18
Kedzierska等：零样本评估揭示单细胞基础模型局限。
引用于： 神经前体样（NPC 样）与少突前体样（OPC 样）胶质瘤细胞状态 · AI 虚拟细胞模型 · 虚拟细胞的验证：基准、基线与批评 · Neftel 式 GBM 状态判定能否跨平台复现？GlioState 再分析（初稿）
Scaling Large Language Models for Next-Generation Single-Cell Analysis
Rizvi SA et al. · bioRxiv · 2025-04-17
C2S-Scale（耶鲁/谷歌）：270亿参数单细胞LLM，含虚拟药物筛选。
Mapping the spatial architecture of glioblastoma from core to edge delineates niche-specific tumor cell states and intercellular interactions
Khan SM et al. · bioRxiv · 2025-04-04
GBM核心到边缘的空间结构。
引用于： 胶质母细胞瘤间充质样（MES 样）细胞状态 · 胶质母细胞瘤单细胞与空间数据集 · Neftel 式 GBM 状态判定能否跨平台复现？GlioState 再分析（初稿）
Single-cell and spatial genomic landscape of non-small cell lung cancer brain metastases.
Tagore S et al. · Nature medicine · 2025-02-27
非小细胞肺癌脑转移单细胞与空间图谱。
Tahoe-100M : A Giga-Scale Single-Cell Perturbation Atlas for Context-Dependent Gene Function and Cellular Modeling
Zhang J et al. · bioRxiv · 2025-02-24
Tahoe-100M：1亿细胞、1100药物×50肿瘤细胞系。
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。
scGPT-spatial: Continual Pretraining of Single-Cell Foundation Model for Spatial Transcriptomics
Wang C, Cui H, Zhang A, Xie R, Goodarzi H, Wang B. · bioRxiv · 2025-02-08
scGPT-spatial：面向空间转录组的持续预训练。
Build the virtual cell with artificial intelligence: a perspective for cancer research.
Yang T, Wang YY, Ma F, Xu BH, Qian HL. · Military Medical Research · 2025-01-27
面向肿瘤研究的虚拟细胞评论（中国团队）。
CZ CELLxGENE Discover: a single-cell data platform for scalable exploration, analysis and modeling of aggregated data.
CZI Cell Science Program et al. · Nucleic acids research · 2025-01-01
CZ CELLxGENE：超1亿细胞的数据平台（含胶质瘤数据集）。
引用于： 胶质母细胞瘤单细胞与空间数据集
Scaling Dense Representations for Single Cell with Transcriptome-Scale Context
Ho N, Ellington CN, Hou J, Addagudi S, Mo S, Tao T, Li D, Zhuang Y, Wang H, Cheng X, Song L, Xing EP. · bioRxiv · 2024-12-03
GenBio AI的AIDO.Cell：全转录组上下文的稠密单细胞模型。
How to build the virtual cell with artificial intelligence: Priorities and opportunities.
Bunne C et al. · Cell · 2024-12-01
奠基性综述：提出“AI虚拟细胞”定义与多尺度、多模态路线图。
引用于： 胶质母细胞瘤间充质样（MES 样）细胞状态 · AI 虚拟细胞模型
A method for in silico exploration of potential glioblastoma multiforme attractors using single-cell RNA sequencing.
Vieira Junior MG, de Almeida Côrtes AM, Gonçalves Carneiro FR, Carels N, Silva FABD. · Scientific reports · 2024-10-29
基于单细胞数据的GBM吸引子计算探索。
GeneCompass: deciphering universal gene regulatory mechanisms with a knowledge-informed cross-species foundation model.
Yang X et al. · Cell research · 2024-10-08
GeneCompass：知识引导的跨物种基础模型（中科院）。
In vivo perturb-seq of cancer and microenvironment cells dissects oncologic drivers and radiotherapy responses in glioblastoma.
Liu SJ et al. · Genome biology · 2024-10-07
GBM体内Perturb-seq：解析驱动基因与放疗反应——脑肿瘤虚拟细胞的关键训练数据类型。
引用于： 胶质母细胞瘤间充质样（MES 样）细胞状态 · 胶质母细胞瘤单细胞与空间数据集 · 胶质母细胞瘤扰动数据：放疗、药物与 CRISPR · 胶质母细胞瘤的治疗诱导可塑性 · Neftel 式 GBM 状态判定能否跨平台复现？GlioState 再分析（初稿）
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。
Large-scale foundation model on single-cell transcriptomics.
Hao M, Gong J, Zeng X, Liu C, Guo Y, Cheng X, Wang T, Ma J, Zhang X, Song L. · Nature methods · 2024-06-06
scFoundation：清华/百图生科的1亿参数单细胞基础模型。
引用于： AI 虚拟细胞模型
Hypoxia coordinates the spatial landscape of myeloid cells within glioblastoma to affect survival.
Haley MJ et al. · Science advances · 2024-05-17
缺氧协调GBM髓系细胞空间格局。
Integrative spatial analysis reveals a multi-layered organization of glioblastoma.
Greenwald AC et al. · Cell · 2024-04-22
Greenwald等：GBM多层次空间组织。
Towards a general-purpose foundation model for computational pathology.
Chen RJ et al. · Nature medicine · 2024-03-19
UNI：通用病理基础模型（含脑肿瘤分型任务）。
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）。
A simple agent-based hybrid model to simulate the biophysics of glioblastoma multiforme cells and the concomitant evolution of the oxygen field.
Saucedo-Mora L, Sanz MÁ, Montáns FJ, Benítez JM. · Computer methods and programs in biomedicine · 2024-01-26
GBM细胞生物物理主体模型。
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。
Universal Cell Embeddings: A Foundation Model for Cell Biology
Rosen Y, Roohani Y, Agrawal A, Samotorcan L, Tabula Sapiens Consortium, Quake SR, Quake SR, Leskovec J. · bioRxiv · 2023-11-29
UCE：跨物种零样本细胞嵌入模型（Leskovec/Quake）。
CellPLM: Pre-training of Cell Language Model Beyond Single Cells
Wen H, Tang W, Dai X, Ding J, Jin W, Xie Y, Tang J. · bioRxiv · 2023-10-05
CellPLM：引入空间关系的细胞语言模型。
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。
Cell2Sentence: Teaching Large Language Models the Language of Biology
Levine D et al. · bioRxiv · 2023-09-14
Cell2Sentence：把细胞转为“句子”供大语言模型学习。
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。
引用于： AI 虚拟细胞模型
Single-cell transcriptomic analyses provide insights into the cellular origins and drivers of brain metastasis from lung adenocarcinoma.
Wang Z, Wang Y, Chang M, Wang Y, Liu P, Wu J, Wang G, Tang X, Hui X, Liu P, Guo X, Xing B, Wang Y, Han Z, Ma W. · Neuro-oncology · 2023-07-01
脑转移细胞起源与驱动。
Transfer learning enables predictions in network biology.
Theodoris CV, Xiao L, Chopra A, Chaffin MD, Al Sayed ZR, Hill MC, Mantineo H, Brydon EM, Zeng Z, Liu XS, Ellinor PT. · Nature · 2023-05-31
Geneformer：支持“计算机模拟敲除”的单细胞基础模型。
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。
引用于： AI 虚拟细胞模型
A single-cell atlas of glioblastoma evolution under therapy reveals cell-intrinsic and cell-extrinsic therapeutic targets.
Wang L, Jung J, Babikir H, Shamardani K, Jain S, Feng X, Gupta N, Rosi S, Chang S, Raleigh D, Solomon D, Phillips JJ, Diaz AA. · Nature cancer · 2022-12-20
治疗下GBM演化单细胞图谱。
引用于： 胶质母细胞瘤间充质样（MES 样）细胞状态 · 胶质母细胞瘤单细胞与空间数据集 · 胶质母细胞瘤的治疗诱导可塑性 · Neftel 式 GBM 状态判定能否跨平台复现？GlioState 再分析（初稿）
The landscape of tumor cell states and spatial organization in H3-K27M mutant diffuse midline glioma across age and location.
Liu I et al. · Nature genetics · 2022-12-05
H3-K27M弥漫中线胶质瘤跨年龄细胞状态与空间组织。
The spatial transcriptomic landscape of non-small cell lung cancer brain metastasis.
Zhang Q, Abdo R, Iosef C, Kaneko T, Cecchini M, Han VK, Li SS. · Nature communications · 2022-10-10
肺癌脑转移空间转录组。
Mapping information-rich genotype-phenotype landscapes with genome-scale Perturb-seq.
Replogle JM et al. · Cell · 2022-06-09
全基因组Perturb-seq（Replogle）：扰动预测标准数据。
Spatially resolved multi-omics deciphers bidirectional tumor-host interdependence in glioblastoma.
Ravi VM et al. · Cancer cell · 2022-06-01
Ravi等：GBM空间多组学揭示肿瘤-宿主相互依存。
引用于： 胶质母细胞瘤单细胞与空间数据集
Single-cell profiling of human dura and meningioma reveals cellular meningeal landscape and insights into meningioma immune response.
Wang AZ et al. · Genome medicine · 2022-05-10
硬脑膜与脑膜瘤单细胞图谱。
scBERT as a Large-scale Pretrained Deep Language Model for Cell Type Annotation of Single-cell RNA-seq Data
Yang F, Wang W, Wang F, Fang Y, Tang D, Huang J, Lu H, Yao J. · bioRxiv · 2021-12-07
scBERT：早期细胞注释预训练模型。
Single-cell RNA-seq reveals that glioblastoma recapitulates a normal neurodevelopmental hierarchy.
Couturier CP et al. · Nature communications · 2020-07-08
GBM重演神经发育层级。
A Patient-Derived Glioblastoma Organoid Model and Biobank Recapitulates Inter- and Intra-tumoral Heterogeneity.
Jacob F et al. · Cell · 2019-12-26
Jacob等：患者来源GBM类器官库。
Single-Cell Transcriptomics in Medulloblastoma Reveals Tumor-Initiating Progenitors and Oncogenic Cascades during Tumorigenesis and Relapse.
Zhang L et al. · Cancer cell · 2019-08-29
髓母细胞瘤起源祖细胞。
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。
Resolving medulloblastoma cellular architecture by single-cell genomics.
Hovestadt V et al. · Nature · 2019-07-24
髓母细胞瘤单细胞结构。
An Integrative Model of Cellular States, Plasticity, and Genetics for Glioblastoma.
Neftel C et al. · Cell · 2019-07-18
Neftel等：GBM四种恶性细胞状态及可塑性——虚拟细胞建模的核心“状态空间”。
引用于： 胶质母细胞瘤间充质样（MES 样）细胞状态 · 神经前体样（NPC 样）与少突前体样（OPC 样）胶质瘤细胞状态 · 胶质母细胞瘤单细胞与空间数据集 · 胶质母细胞瘤的治疗诱导可塑性 · Neftel 式 GBM 状态判定能否跨平台复现？GlioState 再分析（初稿）
Developmental and oncogenic programs in H3K27M gliomas dissected by single-cell RNA-seq.
Filbin MG et al. · Science (New York, N.Y.) · 2018-04-01
Filbin等：H3K27M胶质瘤的发育与致瘤程序。
Decoupling genetics, lineages, and microenvironment in IDH-mutant gliomas by single-cell RNA-seq.
Venteicher AS et al. · Science (New York, N.Y.) · 2017-03-01
Venteicher等：IDH突变胶质瘤单细胞谱系。
Glioma follow white matter tracts: a multiscale DTI-based model.
Engwer C, Hillen T, Knappitsch M, Surulescu C. · Journal of mathematical biology · 2014-09-12
基于DTI的多尺度胶质瘤扩散模型。
Virtual and real brain tumors: using mathematical modeling to quantify glioma growth and invasion.
Swanson KR, Bridge C, Murray JD, Alvord EC. · Journal of the neurological sciences · 2003-12-01
Swanson等：“虚拟脑肿瘤”经典增殖-侵袭模型。
CZI Virtual Cells Platform
Chan Zuckerberg Initiative · web · 日期未注明
CZI虚拟细胞模型平台。
Arc Institute Virtual Cell Initiative
Arc Institute · web · 日期未注明
Arc虚拟细胞计划。
没有符合条件的条目。