🔥 AIVC is a new frontier in computational biology, AIVC stands for Artificial Intelligence Virtual Cell, a technical term originating from a Cell Perspective paper titled "How to Build the Virtual Cell with Artificial Intelligence: Priorities and Opportunities."

💖 If you have any questions, suggestions or improvements, or want to promote your work, please submit your Issues or Pull Requests (PRs).

• [Nature New] Can AI Build a Virtual Cell? Scientists Race to Model Life's Smallest Unit (Nature 2025) [paper] [中文解读]

• [Nature Perspective] Towards Multimodal Foundation Models in Molecular Cell Biology (Nature 2025) [paper] [中文解读]

• [Cell Perspective] Empowering Biomedical Discovery with AI Agents (Cell 2024) [paper] [中文解读]

• [Cell Perspective] How to Build the Virtual Cell with Artificial Intelligence: Priorities and Opportunities (Cell 2024) [paper] [中文解读]

• [Cell Review] Toward a Foundation Model of Causal Cell and Tissue Biology with a Perturbation Cell and Tissue Atlas (Cell 2024) [paper] [中文解读]

• [Symposium] Al Proteomics and Virtual Cell (© by Westlake University 2025) [Media] [中文解读]

• [Report] Projections at the Frontier: Snapshot 2025 (© by Decoding Bio's Team 2025) [Slide] [中文解读]

• [Post] Chan Zuckerberg Initiative's rBio Uses Virtual Cells to Train AI, Bypassing Lab Work (© by Michael Nuñez 2025) [blog]

• [Blog] AI's Next Frontier: Modeling Life Itself (© by Chan Zuckerberg Initiative 2025) [blog] [中文解读]

• [Blog] The State of Research on Virtual Cell Modeling (© by Will Connell 2025) [blog]

• [Blog] What Are Virtual Cells? Learning “Universal Representations” of Life’s Fundamental Unit (© by Elliot Hershberg 2025) [blog]

• [中文 Blog] 什么是虚拟细胞：AI 生物学的 “登月时刻” 和 “苦涩教训” (© by 范阳 2025) [blog]

• [Introduction] Virtual Cells (© by Udara Jay 2025) [blog]

• [Arc Institute] Predicting Cellular Responses to Perturbation across Diverse Contexts with STATE [youtube]

• [Valence Labs] Virtual Cells: Predict, Explain, Discover [youtube]

• [EPFL] Virtual Cells and Digital Twins: AI in Personalized Medicine [youtube]

• [SciLifeLab] Emma Lundberg: AI Virtual Cells Could Revolutionize Biological Science [youtube]

• [Chan Zuckerberg Initiative] AI Virtual Cell Models: How AI is Accelerating Science [youtube]

• [Chan Zuckerberg Initiative] CZI's Vision for AI-Powered "Virtual Cells" [youtube]

• [Podcast] Google DeepMind CEO: We Want to Build a Virtual Cell [youtube]

• [CIGS] High-Throughput Profiling of Chemical-Induced Gene Expression across 93,644 Perturbations (Nature Methods 2025) [paper] [中文解读] [Dataset Link] [code]

• [Tahoe-100M] Tahoe-100M: A Giga-Scale Single-Cell Perturbation Atlas for Context-Dependent Gene Function and Cellular Modeling (bioRxiv 2025) [paper] [中文解读] [code]

• [X-Atlas/Orion] Genome-Wide Perturb-Seq Datasets via a Scalable Fix-Cryopreserve Platform for Training Dose-Dependent Biological Foundation Models (bioRxiv 2025) [paper] [中文解读] [Datasets Link]

• [scBaseCount] scBaseCount: An AI Agent-Curated, Uniformly Processed, and Continually Expanding Single Cell Data Repository (bioRxiv 2025) [paper] [Documentation] [code-scRecounter] [code-SRAgent]

• [Sci-Plex] Massively Multiplex Chemical Transcriptomics at Single-Cell Resolution (Science 2019) [paper] [Datasets Link] [code]

• [scPerturb] scPerturb: Harmonized Single-Cell Perturbation Data (Nature Methods 2024) [paper] [Datasets Link] [code]

• [CMAP LINCS 2020] [Link]

• [Cell Painting Gallery] [Link] [Datasets Overview] [AWS Overview] [Bray Dataset]

• [RxRx from Recursion] [Link]

• [Insight] From Virtual Cell Challenge to Virtual Organs: Navigating the Deep Waters of Medical AI Models (iCell 2025) [paper]

• [Evaluation] Benchmarking and Evaluation of AI Models in Biology: Outcomes and Recommendations from the CZI Virtual Cells Workshop (arXiv 2025) [paper] [中文解读]

• [Challenge] Virtual Cell Challenge: Toward a Turing Test for the Virtual Cell (Cell Commentary 2025) [paper] [Homepage] [Beginner's Guidance]

• [Stack] Stack: In-Context Learning of Single-Cell Biology (bioRxiv) [paper] [code] [ask deepwiki]

• [Pertpy] Pertpy: an End-to-end Framework for Perturbation Analysis (Nature Methods) [paper] [code] [ask deepwiki]

• [Benchmarking] Benchmarking Algorithms for Generalizable Single-Cell Perturbation Response Prediction (Nature Methods) [paper] [code] [ask deepwiki]

• [VCWorld] VCWorld: A Biological World Model for Virtual Cell Simulation (arXiv) [paper] [code] [ask deepwiki]

• [Squidiff] Squidiff: Predicting Cellular Development and Responses to Perturbations using a Diffusion Model (Nature Methods) [paper] [code] [ask deepwiki]

• [Nicheformer] Nicheformer: A Foundation Model for Single-Cell and Spatial Omics (Nature Methods) [paper] [中文解读] [code] [ask deepwiki]

• [ADLF] Active Learning Framework Leveraging Transcriptomics Identifies Modulators of Disease Phenotypes (Science) [paper] [code]

• [Tahoe-x1] Tahoe-x1: Scaling Perturbation-Trained Single-Cell Foundation Models to 3 Billion Parameters (bioRxiv 2025) [paper] [code] [ask deepwiki] [hugging face files]

• [LPM] In Silico Biological Discovery with Large Perturbation Models (Nature Computational Science 2025) [paper] [中文解读] [code] [ask deepwiki]

• [CellNavi] CellNavi Predicts Genes Directing Cellular Transitions by Learning a Gene Graph-Enhanced Cell State Manifold (Nature Cell Biology 2025) [paper] [中文解读] [code] [ask deepwiki]

• [EpiAgent] EpiAgent: Foundation Model for Single-Cell Epigenomics (Nature Methods 2025) [paper] [中文解读] [code] [ask deepwiki]

• [CRISPR-GPT] CRISPR-GPT for Agentic Automation of Gene-Editing Experiments (Nature Biomedical Engineering 2025) [paper] [中文解读] [code] [ask deepwiki]

• [Cell-o1] Cell-o1: Training LLMs to Solve Single-Cell Reasoning Puzzles with Reinforcement Learning (arXiv 2025) [paper] [code] [hugging face] [ask deepwiki]

• [Systema] Systema: A Framework for Evaluating Genetic Perturbation Response Prediction Beyond Systematic Variation (Nature Biotechnology 2025) [paper] [中文解读] [code] [ask deepwiki]

• [RegVelo] RegVelo: Gene-Regulatory-Informed Dynamics of Single Cells (bioRxiv) [paper] [code] [ask deepwiki]

• [PhenoProfiler] PhenoProfiler: Advancing Morphology Representations for Image-based Drug Discovery (Nature Communications 2025) [paper] [code] [webserver] [ask deepwiki]

• [MorphDiff] Prediction of Cellular Morphology Changes under Perturbations with a Transcriptome-Guided Diffusion Model (Nature Communications 2025) [paper] [中文解读] [code] [ask deepwiki]

• [rBio-1] rBio1-Training Scientific Reasoning LLMs with Biological World Models as Soft Verifiers (bioRxiv 2025) [paper] [中文解读] [code] [ask deepwiki]

• [TranscriptFormer] A Cross-Species Generative Cell Atlas across 1.5 Billion Years of Evolution: The Transcriptformer Single-Cell Model (bioRxiv 2025) [paper] [code] [ask deepwiki]

• [CellAtria] An Agentic AI Framework for Ingestion and Standardization of Single-Cell RNA-Seq Data Analysis (bioRxiv 2025) [paper] [中文解读] [code] [ask deepwiki]

• [Scvi-hub] Scvi-hub: An Actionable Repository for Model-Driven Single-Cell Analysis (Nature Methods 2025) [paper] [中文解读] [code] [ask deepwiki]

• [GraphVelo] GraphVelo Allows for Accurate Inference of Multimodal Velocities and Molecular Mechanisms for Single Cells (Nature Communications 2025) [paper] [中文解读] [code] [ask deepwiki]

• [Stereo-Cell] Stereo-Cell: Spatial Enhanced-Resolution Single-Cell Sequencing with High-Density DNA Nanoball-Patterned Arrays (Science 2025) [paper] [中文解读] [code] [ask deepwiki]

• [SToFM] SToFM: A Multi-scale Foundation Model for Spatial Transcriptomics (ICML 2025 Poster) [paper] [中文解读] [code] [ask deepwiki]

• [SpatialAgent] SpatialAgent: An Autonomous AI Agent for Spatial Biology (bioRxiv 2025) [paper] [中文解读] [code] [ask deepwiki]

• [CellFlux] CellFlux: Simulating Cellular Morphology Changes via Flow Matching (ICML 2025 Poster) [paper] [code] [ask deepwiki]

• [CellPB] Benchmarking AI Models for in Silico Gene Perturbation of Cells (bioRxiv 2025) [paper] [code] [ask deepwiki]

• [CellForge] CellForge: Agentic Design of Virtual Cell Models (arXiv 2025) [paper] [中文解读] [code] [ask deepwiki]

• [Brief Communication] Deep-Learning-Based Gene Perturbation Effect Prediction Does Not Yet Outperform Simple Linear Baselines (Nature Methods 2025) [paper] [code] [ask deepwiki]

• [Brief Communication] Limitations of Cell Embedding Metrics Assessed Using Drifting Islands (Nature Biotechnology 2025) [paper] [code] [ask deepwiki]

• [Review] Early-Stage Detection of Donozology at the Molecular Level Using Virtual Cell with AI (PIAS 2025) [paper]

• [GeneAgent] GeneAgent: Self-Verification Language Agent for Gene-Set Analysis Using Domain Databases (Nature Methods 2025) [paper] [code] [ask deepwiki]

• [Theory] Human Interpretable Grammar Encodes Multicellular Systems Biology Models to Democratize Virtual Cell Laboratories (Cell 2025) [paper] [code] [ask deepwiki]

• [GREmLN] GREmLN: A Cellular Regulatory Network-Aware Transcriptomics Foundation Model (bioRxiv 2025) [paper] [中文解读] [code] [ask deepwiki]

• [CellVoyager] CellVoyager: AI CompBio Agent Generates New Insights by Autonomously Analyzing Biological Data (bioRxiv 2025) [paper] [中文解读] [code] [ask deepwiki]

• [CausCell] Causal Disentanglement for Single-Cell Representations and Controllable Counterfactual Generation (Nature Communications 2025) [paper] [中文解读] [code] [ask deepwiki]

• [CLIP^n] Transitive Prediction of Small-Molecule Function through Alignment of High-Content Screening Resources (Nature Biotechnology 2025) [paper] [code] [ask deepwiki]

• [DrugPT] DrugPT: A Flexible Framework for Integrating Gene and Chemical Representations in Perturbation Modeling (bioRxiv 2025) [paper]

• [OmniPert] OmniPert: A Deep Learning Foundation Model for Predicting Responses to Genetic and Chemical Perturbations in Single Cancer Cells (bioRxiv 2025) [paper]

• [UNAGI] A Deep Generative Model for Deciphering Cellular Dynamics and in Silico Drug Discovery in Complex Diseases (Nature Biomedical Engineering 2025) [paper] [code] [ask deepwiki]

• [OmiCLIP] A Visual–Omics Foundation Model to Bridge Histopathology with Spatial Transcriptomics (Nature Methods 2025) [paper] [code] [ask deepwiki]

• [Biomni] Biomni: A General-Purpose Biomedical AI Agent (bioRxiv 2025) [paper] [code] [ask deepwiki]

• [OCTO-vc] OCTO-vc: Virtual Cells in Real Tissue (© by Noetik 2025) [technical report] [online demonstration]

• [STATE] Predicting Cellular Responses to Perturbation across Diverse Contexts with STATE (bioRxiv 2025) [paper] [code] [ask deepwiki]

• [UniPert-G2CP] Genetic-To-Chemical Perturbation Transfer Learning through Unified Multimodal Molecular Representations (bioRxiv 2025) [paper] [code] [ask deepwiki]

• [UniCure] Unicure: A Foundation Model for Predicting Personalized Cancer Therapy Response (bioRxiv 2025) [paper] [code] [ask deepwiki]

• [Cell-GraphCompass] Cell-GraphCompass: Modeling Single Cells with Graph Structure Foundation Model (National Science Review 2025) [paper] [code] [ask deepwiki]

• [scPRINT] scPRINT: Pre-training on 50 Million Cells Allows Robust Gene Network Predictions (Nature Communications 2025) [paper] [code] [ask deepwiki]

• [CellFM] CellFM: A Large-Scale Foundation Model Pre-trained on Transcriptomics of 100 Million Human Cells (Nature Communications 2025) [paper] [中文解读] [code] [ask deepwiki]

• [C2S-Scale] C2S-Scale: Scaling Large Language Models for Next-Generation Single-Cell Analysis (bioRxiv 2025) [paper] [中文解读] [code] [ask deepwiki]

• [scNET] scNET: Learning Context-Specific Gene and Cell Embeddings by Integrating Single-Cell Gene Expression Data with Protein–Protein Interactions (Nature Methods 2025) [paper] [code] [ask deepwiki]

• [Token-Mol 1.0] Token-Mol 1.0: Tokenized Drug Design with Large Language Models (Nature Communications 2025) [paper] [code] [ask deepwiki]

• [Comment] Virtual Cells for Predictive Immunotherapy (Nature Biotechnology Comment 2025) [paper]

• [Recursion] Virtual Cells: Predict, Explain, Discover (arXiv 2025) [paper]

• [CellFlow] CellFlow Enables Generative Single-Cell Phenotype Modeling with Flow Matching (bioRxiv 2025) [paper] [code] [ask deepwiki]

• [Prophet] Scalable and Universal Prediction of Cellular Phenotypes (bioRxiv 2025) [paper] [code] [ask deepwiki]

• Evaluating Feature Extraction in Ovarian Cancer Cell Line Co-Cultures Using Deep Neural Networks (Communications Biology 2025) [paper]

• [ProteinTalks] A Perturbation Proteomics-Based Foundation Model for Virtual Cell Construction (bioRxiv 2025) [paper] [中文解读] [code] [ask deepwiki]

• Grow AI Virtual Cells: Three Data Pillars and Closed-Loop Learning (Cell Research 2025) [paper] [中文解读]

• Build the Virtual Cell with Artificial Intelligence: A Perspective for Cancer Research (Military Medical Research 2025) [paper]

• [PS] Decoding Heterogeneous Single-Cell Perturbation Responses (Nature Cell Biology 2025) [paper] [code] [ask deepwiki]

• [Mixscale] Systematic Reconstruction of Molecular Pathway Signatures Using Scalable Single-Cell Perturbation Screens (Nature Cell Biology 2025) [paper] [code] [ask deepwiki]

• [GET] A Foundation Model of Transcription across Human Cell Types (Nature 2025) [paper] [code] [ask deepwiki]

• [GEARS] Predicting transcriptional outcomes of novel multigene perturbations with GEARS (Nature Communications 2024) [paper] [code] [ask deepwiki]

• [TranSiGen] Deep Representation Learning of Chemical-Induced Transcriptional Profile for Phenotype-Based Drug Discovery (Nature Communications 2024) [paper] [code] [ask deepwiki]

• [GenePT] Simple and Effective Embedding Model for Single-Cell Biology Built from ChatGPT (Nature Biomedical Engineering 2024) [paper] [code] [ask deepwiki]

• [SCimilarity] A Cell Atlas Foundation Model for Scalable Search of Similar Human Cells (Nature 2024) [paper] [code] [ask deepwiki]

• [scLong] scLong: A Billion-Parameter Foundation Model for Capturing Long-Range Gene Context in Single-Cell Transcriptomics (bioRxiv 2024) [paper] [code] [ask deepwiki]

• [scFoundation] Large-Scale Foundation Model on Single-Cell Transcriptomics (Nature Methods 2024) [paper] [code] [ask deepwiki]

• [scGPT] scGPT: Toward Building a Foundation Model for Single-Cell Multi-Omics Using Generative AI (Nature Methods 2024) [paper] [code] [ask deepwiki]

• [TamGen] TamGen: Drug Design with Target-Aware Molecule Generation through a Chemical Language Model (Nature Communications 2024) [paper] [code] [ask deepwiki]

• [GeneCompass] GeneCompass: Deciphering Universal Gene Regulatory Mechanisms with a Knowledge-Informed Cross-Species Foundation Model (Cell Research 2024) [paper] [code] [ask deepwiki]

• [scTab] scTab: Scaling Cross-Tissue Single-Cell Annotation Models (Nature Communications 2024) [paper] [code] [ask deepwiki]

• [SATURN] Toward Universal Cell Embeddings: Integrating Single-Cell RNA-Seq Datasets across Species with SATURN (Nature Methods 2024) [paper] [code] [ask deepwiki]

• [UCE] Universal Cell Embeddings: A Foundation Model for Cell Biology (bioRxiv 2024) [paper] [code] [ask deepwiki]

• [Cell2Sentence] Cell2Sentence: Teaching Large Language Models the Language of Biology (ICML 2024 Poster) [paper] [code] [ask deepwiki]

• [LangCell] LangCell: Language-Cell Pre-training for Cell Identity Understanding (ICML 2024 Poster) [paper] [code] [ask deepwiki]

• [CellPLM] CellPLM: Pre-training of Cell Language Model beyond Single Cells (ICLR 2024 Poster) [paper] [code] [ask deepwiki]

• [斯坦福博士学位论文] Engineering Cells Using Artificial Intelligence (© by Yusuf Roohani 2024) [paper] [GitHub Homepage] [Arc's Machine Learning Group Leader]

• [Geneformer] Transfer Learning Enables Predictions in Network Biology (Nature 2023) [paper] [code] [ask deepwiki]

• [CellOT] Learning Single-Cell Perturbation Responses Using Neural Optimal Transport (Nature Methods 2023) [paper] [code] [ask deepwiki]

• [tGPT] Generative Pretraining from Large-Scale Transcriptomes for Single-Cell Deciphering (iScience 2023) [paper] [code] [ask deepwiki]

• Building the Next Generation of Virtual Cells to Understand Cellular Biology (Biophysical Journal 2023) [paper]

• [Research Highlight] Simulating a Whole Cell (Nature Methods 2022) [paper]

• [Comment] Personalized Medicine: Time for One-Person Trials (Nature Comment 2015) [paper]

• [Theory] A Whole-Cell Computational Model Predicts Phenotype from Genotype (Cell 2012) [paper]

• [Virtual Cell] The Virtual Cell —— A Candidate Co-Ordinator for "Middle-Out" Modelling of Biological Systems (BIB 2009) [paper]

• [VCell 7.7] Virtual Cell Modelling and Simulation Software Environment (IET Systems Biology 2008) [paper] [software]

• Quantitative Cell Biology with the Virtual Cell (Trends in Cell Biology 2003) [paper]

• [Review] The Virtual Cell: A Software Environment for Computational Cell Biology (Trends in Biotechnology 2001) [paper]

• [Opinion] Whole-Cell Simulation: A Grand Challenge of the 21st Century (Trends in Biotechnology 2001) [paper]