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 hematopoietic stem cells at 10X efficiency vs. reprogramming via iPSC
PAPERS
Ronquist S, Patterson G, Muir LA, Lindsly S, Chen H, Brown M, Wicha MS, Bloch A, Brockett R, Rajapakse I. "Algorithm for cellular reprogramming." Proceedings of the National Academy of Sciences. 2017 Nov 7;114(45):11832-7. Data-guided Control (DGC) Supporting Information
Chen H, Chen J, Muir LA, Ronquist S, Meixner W, Ljungman M, Ried T, Smale S, Rajapakse I. "Functional Organization of the Human 4D Nucleome. " Proceedings of the National Academy of Sciences 112.26 (2015): 8002-8007. Supporting Information
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He, Zhen, et al. "Mosaic integration and knowledge transfer of single-cell multimodal data with MIDAS." Nature Biotechnology (2024): 1-12.
Li, Q., Hu, Z., Wang, Y., Li, L., Fan, Y., King, I., ... & Li, Y. (2024). "Progress and Opportunities of Foundation Models in Bioinformatics." arXiv preprint arXiv:2402.04286.
K. Kawaharazuka, T. Matsushima, A. Gambardella, J. Guo, C. Paxton, and A. Zeng, “Real-World Robot Applications of Foundation Models: A Review.” arXiv, Feb. 08, 2024
Gemini Team et al., “Gemini: A Family of Highly Capable Multimodal Models.” arXiv, Dec. 18, 2023
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W. Hou and Z. Ji, “Assessing GPT-4 for cell type annotation in single-cell RNA-seq analysis,” Nat Methods, pp. 1–4, Mar. 2024
H. Cui et al., “scGPT: toward building a foundation model for single-cell multi-omics using generative AI,” Nat Methods, pp. 1–11, Feb. 2024
V. Sharma and V. Raman, “A reliable knowledge processing framework for combustion science using foundation models,” Energy and AI, vol. 16, p. 100365, May 2024
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Schiebinger, Geoffrey, et al. "Optimal-transport analysis of single-cell gene expression identifies developmental trajectories in reprogramming." Cell 176.4 (2019): 928-943.
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Szklarczyk, Damian, et al. "STRING v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets." Nucleic acids research 47.D1 (2019): D607-D613.
OTHER RESOURCES
Graph Attention Networks: https://petar-v.com/GAT/
NVIDIA and other related sites etc....
