RESEARCH / SOURCE INDEX

Research index

Original publication titles and primary sources, organized without invented English summaries. This is a bibliographic index: source availability or peer review alone does not establish clinical validation.

37 studies14 tracking entriesUpdated 2026-10-16

Detailed critical notes and limitations currently remain available in the Chinese evidence library. Additional English perspectives will appear only after author review.

01StudyPreprint

Alpha Spatial: Language-guided prediction of single-cell spatial gene expression from histology

Xi Yang, Ziyi Guo, Xuyuan Guo, Wan Wang, Bowen Bai, Xingran Liu, Chao Zhang, Yufei He, Yuncai Liu · bioRxiv · 2026-10-15

Research index

Alpha Spatial: Language-guided prediction of single-cell spatial gene expression from histology

Meet some of the 2026 Virtual Cell Challenge competitors

Rebuilding the Brainstem to Study Diffuse Midline Glioma: Human brainstem organoid (BrO) and organ-on-chip platforms for translational paediatric neuro-oncology

Spatiotemporal AI-based modeling of gene regulation and variant effects in the developing human brain using Seal

A multimodal precision oncology platform integrating genomics, single-cell transcriptomics, and functional drug screening expands therapeutic options in pediatric brain tumors

Divergent genomic evolution in astrocytomas and oligodendrogliomas

SpatialZoomer: multi-scale feature analysis of spatial transcriptomics

A high-resolution protein-RNA binding atlas for structure-aware interaction prediction and post-transcriptional regulatory modeling

A split-control criterion for few-shot adaptation in single-cell perturbation prediction

BioMod: Biological Module Tokenization for Single-Cell Foundation Modeling

Learning Perturbation-Specific Representations through Conditional Energy Prior for Cellular Response Prediction

A Clearer Map of RNA-Binding Proteins with eclair-CLIP

A Multi-Omic Phenobank Reveals Axes of Glioblastoma Growth, Invasion, and Therapeutic Vulnerability.

CloneOT: predicting clone-specific perturbation responses with lineage-supervised neural inverse optimal transport

Dynamic Graph Prior-Guided Latent Adaptation for Generalizable Single-Cell Perturbation Response Prediction

Point-Process Modelling of Cell-Type Interaction Structure in CosMx Glioma Data for Hypothesis-Driven Tumor Inference from scRNA-seq

PIE: Generalizing perturbation effects across unseen perturbations, contexts and datasets

Deep learning perturbation models can outperform baselines on calibrated metrics

Tahoe-100M: Mapping drug-induced molecular phenotypes at single-cell resolution

An operational perturbation proteomics-based virtual cell model

Predicting cellular responses to perturbation across diverse contexts with State

The 2026 Virtual Cell Challenge: predicting perturbation responses in cell contexts a model has never seen

SAGE-FM: A lightweight and interpretable spatial transcriptomics foundation model.

Digital twins for in vivo metabolic flux estimations in patients with brain cancer.

Benchmarking algorithms for generalizable single-cell perturbation response prediction

Nicheformer: a foundation model for single-cell and spatial omics

Charting the single-cell and spatial landscape of IDH-wild-type glioblastoma with GBmap.

Accelerating AI in Biology With Community-Driven Benchmarks

Yusuf Roohani, Arc’s Associate Director of Machine Learning, on designing the architecture behind a virtual cell

Deep-learning-based gene perturbation effect prediction does not yet outperform simple linear baselines

Pan-cancer human brain metastases atlas at single-cell resolution.

Single-cell and spatial genomic landscape of non-small cell lung cancer brain metastases.

Glioblastoma Cortical Organoids Recapitulate Cell-State Heterogeneity and Intercellular Transfer.

A foundation model of transcription across human cell types

In vivo perturb-seq of cancer and microenvironment cells dissects oncologic drivers and radiotherapy responses in glioblastoma.

Priscilla Chan, Stephen Quake Discuss Accelerating Science With AI at Stanford’s Big Ideas in Medicine

Integrative spatial analysis reveals a multi-layered organization of glioblastoma.

scGPT: toward building a foundation model for single-cell multi-omics using generative AI

Predicting transcriptional outcomes of novel multigene perturbations with GEARS

Transfer learning enables predictions in network biology

Spatial transcriptomics reveals niche-specific enrichment and vulnerabilities of radial glial stem-like cells in malignant gliomas.

Interactions between cancer cells and immune cells drive transitions to mesenchymal-like states in glioblastoma.

Integrated regulatory models for inference of subtype-specific susceptibilities in glioblastoma.

An Integrative Model of Cellular States, Plasticity, and Genetics for Glioblastoma.

2026 SNO/ASCO CNS Metastases Conference

31st Society for Neuro-Oncology Annual Meeting & Education Day

AACR Special Conference in Cancer Research: Brain Cancer

EANO 2026 — 21st Meeting & Educational Day

Laboratory for Proteome Complexity Science — Publications

Mapping the Spatial and Temporal Utilization of Cancer Cell States and Building Human-Interpretable Models of Cell State Regulation by the Micro and Macro-Environment

Neuro-Oncology: The Podcast