TwinCell Blueprint: Foundation for AI-Assisted Cell Reprogramming

We propose to couple our automated in vitro cellular reprogramming platform with a new compositional, multimodal AI/LLM modeling and control approach to demonstrate Direct Reprogramming of human fibroblasts to cell type X at 10X efficiency vs. reprogramming via iPSC. This project is funded by DARPA.

PAPERS

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55. Simon, Elana, Kyle Swanson, and James Zou. "Language models for biological research: a primer." Nature Methods 21.8 (2024): 1422-1429. 

56. Rood, Jennifer E., Anna Hupalowska, and Aviv Regev. "Toward a foundation model of causal cell and tissue biology with a Perturbation Cell and Tissue Atlas." Cell 187.17 (2024): 4520-4545. 

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58. Ivanov, Igor. "BioLP-bench: Measuring understanding of AI models of biological lab protocols." bioRxiv (2024): 2024-08. 

59. H. Chen et al., “Quantized multi-task learning for context-specific representations of gene network dynamics,” Aug. 19, 2024

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71. Schaefer, Moritz, Peter Peneder, Daniel Malzl, Mihaela Peycheva, Jake Burton, Anna Hakobyan, Varun Sharma et al. "Multimodal learning of transcriptomes and text enables interactive single-cell RNA-seq data exploration with natural-language chats." bioRxiv (2024): 2024-10. 

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OTHER RESOURCES

Graph Attention Networks: https://petar-v.com/GAT/

NVIDIA  and other related sites etc....