Research Articles
Single-Cell Foundation Models: Revolutionizing Drug Sensitivity Prediction in Precision Oncology
This article explores the transformative role of single-cell foundation models (scFMs) in predicting drug sensitivity, a critical challenge in precision medicine.
Decoding Cellular Logic: A Comprehensive Guide to Single-Cell Gene Regulatory Network Inference
This article provides a thorough exploration of gene regulatory network (GRN) inference from single-cell data, a key methodology for understanding the transcriptional programs that define cell identity and function.
In Silico Perturbation Modeling with Single-Cell Foundation Models: A New Frontier for Predictive Biology
In silico perturbation modeling using single-cell foundation models (scFMs) promises to revolutionize biological discovery and therapeutic development by predicting cellular responses to genetic and chemical interventions.
A Comprehensive Guide to Cell Type Annotation with scGPT: From Foundation Models to Clinical Applications
This article provides researchers, scientists, and drug development professionals with a complete framework for implementing scGPT for single-cell RNA sequencing annotation.
Decoding the Cell: How Biological Knowledge is Represented in Single-Cell Foundation Model Embeddings
Single-cell Foundation Models (scFMs) are revolutionizing biological research by learning generalizable representations from vast single-cell genomics datasets.
Tokenization Strategies for Single-Cell RNA Sequencing Data in Foundation Models: A Comprehensive Guide
Single-cell foundation models (scFMs) are transforming biomedical research by enabling large-scale analysis of cellular heterogeneity.
Decoding Cellular Diversity: How Single-Cell Foundation Models Capture Heterogeneity in Health and Disease
Single-cell Foundation Models (scFMs) are revolutionizing our ability to decipher cellular heterogeneity by learning universal representations from millions of single-cell transcriptomes.
Foundation Models for Single-Cell Multi-Omics Integration: A New Paradigm for Cellular Biology and Precision Medicine
The emergence of single-cell multi-omics technologies has created an urgent need for computational frameworks capable of integrating complex, high-dimensional data.
Self-Supervised Learning in Single-Cell Omics: From Foundation Models to Clinical Translation
This article provides a comprehensive exploration of self-supervised learning (SSL) and foundation models, which are revolutionizing the analysis of single-cell omics data.
Single-Cell Foundation Models: A Comprehensive Guide for Biomedical Researchers
This article provides a comprehensive overview of single-cell foundation models (scFMs), large-scale AI systems pretrained on millions of single-cell transcriptomes to decipher the fundamental 'language' of biology.