ArticleiMeta2025
scRiskCell: A single-cell framework for quantifying islet risk cells and their adaptive dynamics in type 2 diabetes.
Article in iMeta, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
19 citing papers in PubMed.
- DECANT: decoupling mechanism from context in single-cell drug perturbation representation.Bioinformatics (Oxford, England) · 2026Article
- Integrated Transcriptomic Analyses Identify Four Prognosis-Associated Genes in Hepatocellular Carcinoma.International journal of molecular sciences · 2026Article
- AGCECDA: attention-guided heterogeneous graph collaborative embedding for circRNA-drug sensitivity association prediction.BMC biology · 2026Article
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- Multidimensional cfRNA response modeling identifies a 5-gene pair signature for high-robust pulmonary tuberculosis diagnosis.iScience · 2026Article
- A large-scale single-cell transcriptomic atlas indicates the immune panorama of influenza A infection.iMeta · 2026Article
- PTBD: a machine learning-based non-invasive diagnostic model for pulmonary tuberculosis using large-scale blood transcriptomes.BMC biology · 2026Article
- CFGSCDSA: Predicting circRNA-drug sensitivity associations based on collaborative feature learning and graph structure learning.PLoS computational biology · 2026Article
- PepLM-GNN: A graph neural network framework leveraging pre-trained language models for peptide-protein binding prediction.PLoS computational biology · 2026Article
- DeepSGE: predicting spatial gene expression using residual network with efficient channel attention and dynamic graph attention network.BMC genomics · 2026Article
- Artificial intelligence-powered prediction of diabetic complications: from clinical data to molecular omics.Briefings in bioinformatics · 2026Article
- DFL-MHC: MHC identification model based on dual-stage training and multi-view feature fusion.Frontiers in genetics · 2026Article
- Protective role of aqueousFrontiers in endocrinology · 2026Article
- DSCA-HLAII: A dual-stream cross-attention model for predicting peptide-HLA class II interaction and presentation.PLoS computational biology · 2026Article
- A Multi-Omics Integration Framework with Automated Machine Learning Identifies Peripheral Immune-Coagulation Biomarkers for Schizophrenia Risk Stratification.International journal of molecular sciences · 2025Article
- Article
- Interpretable machine learning-guided single-cell mapping deciphers multi-lineage pancreatic dysregulation in type 2 diabetes.Cardiovascular diabetology · 2025Article
- BertADP: a fine-tuned protein language model for anti-diabetic peptide prediction.BMC biology · 2025Article
- Deciphering the Molecular Mechanisms of Polycystic Ovary Syndrome and Flaxseed Therapy Through Transcriptomics and Machine Learning.IET systems biologyArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
scRiskCell is an interpretable intelligent computational framework that leverages nearly 500,000 islet cell expression profiles from 106 donors across different continuous disease states. By calculating the intrinsic relationship between donor disease states and cell expression profiles, it assigns a pseudo-cell state index to each cell. Sorting the pseudo-indexes of cells enables the identification of risk cells truly disrupted by the disease. Importantly, scRiskCell reveals the dynamic aggregation pattern of risk cells during disease progression, providing mechanistic insights for early disease prediction and clinical dynamic monitoring of disease progression.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.