AI virtual cells
Cell states, perturbation responses, and cell foundation models. Explore research source records, company profiles, and current public reviewed events with sources and dates preserved.
Topic labels are automated discovery categories for finding related material. They do not establish a company’s capabilities, causality, or clinical efficacy.
Research and industry source records
Isomorphic Labs joins the Virtual Biology Initiative to build foundational data for AI models to predict and treat disease
Isomorphic Labs official announcements · Indexed industry source record · Source published: Wed Oct 07 2026 00:00:00 GMT+0000 (Coordinated Universal Time) · Indexed here: Thu Oct 08 2026 09:07:57 GMT+0000 (Coordinated Universal Time)
Listen: Spotify Apple Podcasts Convened by Biohub, participating organisations are investing funding, data, computation and new measurement technology - the largest coordinated commitment to generating AI-ready biologica
CellART: a unified framework for extracting single-cell information from high-resolution spatial transcriptomics.
PubMed / NCBI E-utilities · Indexed academic record · Source published: Mon Oct 05 2026 00:00:00 GMT+0000 (Coordinated Universal Time) · Indexed here: Thu Oct 08 2026 05:41:45 GMT+0000 (Coordinated Universal Time)
Recent advances in spatial transcriptomics (ST) have achieved subcellular spatial resolution, yet existing platforms either capture sparse transcript counts per spot or measure only a limited number of genes, complicatin
CytoVI: deep generative modeling of antibody-based single cell data.
PubMed / NCBI E-utilities · Indexed academic record · Source published: Wed Sep 30 2026 00:00:00 GMT+0000 (Coordinated Universal Time) · Indexed here: Thu Oct 08 2026 09:09:22 GMT+0000 (Coordinated Universal Time)
Antibody-based single-cell technologies, such as flow cytometry, mass cytometry and CITE-seq, have become widely used in clinical diagnostics and basic research; however, their analysis is complicated by technical noise,
4D spatiotemporal landscape of mitochondrial phenotypes across cellular states unlocked through representation learning.
PubMed / NCBI E-utilities · Indexed academic record · Source published: Thu Sep 10 2026 00:00:00 GMT+0000 (Coordinated Universal Time) · Indexed here: Thu Oct 08 2026 09:08:08 GMT+0000 (Coordinated Universal Time)
Mitochondria are four-dimensional (4D: x, y, z, and time) organelles essential for cellular function. Characterizing their 4D phenotypic landscape across diverse cellular states requires both 4D imaging and analytical fr
An operational perturbation proteomics-based virtual cell model.
PubMed / NCBI E-utilities · Indexed academic record · Source published: Wed Sep 09 2026 00:00:00 GMT+0000 (Coordinated Universal Time) · Indexed here: Thu Oct 08 2026 09:08:08 GMT+0000 (Coordinated Universal Time)
Artificial intelligence-empowered virtual cell models represent an emerging approach for in silico drug discovery 1-3 , yet most existing approaches lack large-scale, time-resolved perturbation proteomics data and interp
Deep-learning-based de novo discovery and design of therapeutics that reverse disease-associated transcriptional phenotypes.
Europe PMC REST API · Indexed academic record · Source published: Tue Mar 17 2026 00:00:00 GMT+0000 (Coordinated Universal Time) · Indexed here: Thu Oct 08 2026 09:08:13 GMT+0000 (Coordinated Universal Time)
Identifying drugs that reverse disease-associated transcriptomic features has been widely explored for drug repurposing, but its potential for de novo drug discovery remains underexplored. Here, we present gene expressio
Accelerating Single-Cell Deep Learning with scDataset and Tahoe-100M
Tahoe official blog RSS · Indexed industry source record · Source published: Wed Jul 16 2025 18:56:30 GMT+0000 (Coordinated Universal Time) · Indexed here: Thu Oct 08 2026 07:03:31 GMT+0000 (Coordinated Universal Time)
As single-cell technologies scale, biology is entering a new era—one where the volume and complexity of data now rival those in fields like computer vision and natural language processing. Among the most powerful advance
How to build the virtual cell with artificial intelligence: Priorities and opportunities.
Europe PMC REST API · Indexed academic record · Source published: Sun Dec 01 2024 00:00:00 GMT+0000 (Coordinated Universal Time) · Indexed here: Thu Oct 08 2026 09:08:13 GMT+0000 (Coordinated Universal Time)
Cells are essential to understanding health and disease, yet traditional models fall short of modeling and simulating their function and behavior. Advances in AI and omics offer groundbreaking opportunities to create an
Interpretable spatially aware dimension reduction of spatial transcriptomics with STAMP.
Europe PMC REST API · Indexed academic record · Source published: Tue Oct 15 2024 00:00:00 GMT+0000 (Coordinated Universal Time) · Indexed here: Thu Oct 08 2026 09:08:13 GMT+0000 (Coordinated Universal Time)
Spatial transcriptomics produces high-dimensional gene expression measurements with spatial context. Obtaining a biologically meaningful low-dimensional representation of such data is crucial for effective interpretation
Current public reviewed events
Isomorphic Labs 加入 Virtual Biology Initiative
Wed Oct 07 2026 00:00:00 GMT+0000 (Coordinated Universal Time) · 1 currently public evidence items
据 Isomorphic Labs 官方公告，加入由 Biohub 召集的 Virtual Biology Initiative，参与组织将投入数据、计算与测量技术。Biohub 尚未完成本库实体归属核验，暂不绘制关系边。
Companies with related public source records
- Isomorphic Labs · AI, models, and data · 英国/美国
- Tahoe Therapeutics · AI, models, and data · 美国
Reader guides: from sources to conclusions
Compare models by task and follow collaborations through evidence. Each guide includes original sources and a review date.
How should we compare virtual cells, AI models, and companies?
Compare single-cell models, structure prediction, and protein design by inputs, outputs, tasks, and validation conditions. Distinguish model papers from company capabilities.
Reader guide · updated 2026-10-08
How to read weekly AI drug discovery updates: companies, research, and coverage gaps
Build a weekly reading routine, distinguish announcements, papers, and clinical results, and understand this site’s weekly indexing window, denominators, and source coverage.
Reader guide · updated 2026-10-08