Research Articles
Clearing the Static: A Comprehensive Guide to Mitigating Technical Noise in Single-Cell Foundation Models
Single-cell RNA sequencing has revolutionized biology, but its potential is clouded by technical noise, including dropout events and batch effects.
Building Robust Single-Cell Foundation Models: A Strategic Framework to Counter Dataset Shift in Biomedical Research
Single-cell foundation models (scFMs) represent a paradigm shift in analyzing cellular heterogeneity, yet their real-world application is hampered by a critical vulnerability: performance degradation under dataset shift.
Strategic Approaches to Optimize Computational Efficiency in Large-Scale Single-Cell Foundation Models
The rapid expansion of single-cell genomics, with repositories now exceeding 100 million cells, has created an urgent need for computationally efficient analysis frameworks.
Single-Cell Clustering Algorithms for Transcriptomic Data: A 2025 Benchmarking and Practical Guide
This article provides a comprehensive overview of single-cell RNA sequencing (scRNA-seq) clustering algorithms, essential tools for unraveling cellular heterogeneity.
Zero-Shot Learning with Single-Cell Foundation Models: Current State, Challenges, and Future Directions
Single-cell foundation models (scFMs), pretrained on millions of single-cell transcriptomes, promise to revolutionize biological discovery by enabling zero-shot learning—applying model knowledge to new data without task-specific training.
Gene Function Prediction with Single-Cell Foundation Models: A Practical Guide to Embeddings, Applications, and Benchmarking
This article provides a comprehensive overview of the rapidly evolving field of gene function prediction using single-cell Foundation Model (scFM) embeddings.
scBERT for Cell Type Annotation: A Comprehensive Guide to Foundational Models in Single-Cell RNA-Seq Analysis
This article provides a thorough exploration of scBERT, a transformer-based model revolutionizing cell type annotation in single-cell RNA sequencing data.
Single-Cell Foundation Models: Revolutionizing Multi-Omics Data Integration for Biomedical Research
This article provides a comprehensive exploration of single-cell foundation models (scFMs) and their transformative role in multi-omics data integration.
Batch Integration with scFoundation Embeddings: A Comprehensive Guide for Robust Single-Cell Analysis
This article provides a comprehensive guide for researchers and bioinformaticians on leveraging scFoundation, a large-scale single-cell foundation model, for batch integration tasks.
Decoding Cellular Diversity: How Single-Cell Foundation Models Are Revolutionizing Biomedical Research
Single-cell foundation models (scFMs) are emerging as transformative artificial intelligence tools for deciphering cellular heterogeneity in biomedical research.