scGPT: Gene Regulatory Network Inference on Pre-trained Models
Cui et al.
scGPT (v0.1.7) is a foundation model for single-cell biology, based on generative pre-trained transformers trained on a vast repository of over 33 million cells. The scGPT model demonstrates the ability to extract valuable biological insights and can be further optimized through transfer learning for various downstream applications, including cell-type annotation, multi-batch integration, genetic perturbation prediction, and gene network inference.
Example use case: Gene regulatory network inference
Technology: Transformers
Limitation:
- Some of the parameters were kept default. Please see this page for more details.
Citation:
scGPT: Towards Building a Foundation Model for Single-Cell Multi-omics Using Generative AI Haotian Cui, Chloe Wang, Hassaan Maan, Kuan Pang, Fengning Luo, Bo Wang
bioRxiv 2023.04.30.538439; doi: https://doi.org/10.1101/2023.04.30.538439
Released: Jul-19-2023
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