scGPT: Towards Building a Foundation Model for Single-Cell Multi-omics Using Generative AI
University Health Network · University of Toronto · +1 more institution
Abstract
Abstract Generative pre-trained models have achieved remarkable success in various domains such as natural language processing and computer vision. Specifically, the combination of large-scale diverse datasets and pre-trained transformers has emerged as a promising approach for developing foundation models. Drawing parallels between linguistic constructs and cellular biology — where texts comprise words, similarly, cells are defined by genes — our study probes the applicability of foundation models to advance cellular biology and genetics research. Utilizing the burgeoning single-cell sequencing data, we have pioneered the construction of a foundation model for single-cell biology, scGPT, which is based on…
Citation impact
- FWCI
- —
- Percentile
- —
- References
- 83
Authors
6- HCHaotian Cui
University Health Network, University of Toronto, Vector Institute
- CWChloe Wang
University Health Network, University of Toronto, Vector Institute
- HMHassaan Maan
University Health Network, University of Toronto, Vector Institute
- KPKuan Pang
University of Toronto, Vector Institute
- FLFengning Luo
University of Toronto, Vector Institute
Topics & keywords
- Generative grammar
- Inference
- Synthetic biology
- Computer science
- Transformer
- Systems biology
- Artificial intelligence
- Generative model