The Virtual Genome

Papers

1. Avsec, Žiga, Natasha Latysheva, Jun Cheng, Guido Novati, Kyle R. Taylor, Tom Ward, Clare Bycroft et al. "Advancing regulatory variant effect prediction with AlphaGenome." Nature 649, no. 8099 (2026): 1206-1218.

2. Bunne, Charlotte, Yusuf Roohani, Yanay Rosen, Ankit Gupta, Xikun Zhang, Marcel Roed, Theo Alexandrov, et al. “How to build the virtual cell with artificial intelligence: Priorities and opportunities.” Cell 187, no. 26 (2024): 7045–7063.

3. Avsec, Žiga, Natasha Latysheva, Jun Cheng, Guido Novati, Kyle R. Taylor, Tom Ward, Clare Bycroft, et al. "Advancing regulatory variant effect prediction with AlphaGenome." Nature 649, no. 8099 (2026): 1206-1218.

4. Richter, Till, Weixu Wang, Alessandro Palma, and Fabian J. Theis. "Generative models of cell dynamics: from Neural ODEs to flow matching." Communications Biology 9 (2026): 352.

5. Bunne, Charlotte, Yusuf Roohani, Yanay Rosen, Ankit Gupta, Xikun Zhang, Marcel Roed, Theo Alexandrov, et al. "How to build the virtual cell with artificial intelligence: Priorities and opportunities." Cell 187, no. 26 (2024): 7045-7063.

6. Liu, Zhiyuan, Yujie Chen, Qimin Xia, Menghan Liu, Heming Xu, Yi Chi, Yujing Deng, and Dong Xing. “Linking genome structures to functions by simultaneous single-cell Hi-C and RNA-seq.” Science 380 (2023): 1070–1076.

7. Maass, Philipp G., A. Rasim Barutcu, Catherine L. Weiner, and John L. Rinn. “Inter-chromosomal contact properties in live-cell imaging and in Hi-C.” Molecular Cell 69 (2018): 1039–1045.

8. Abbas, Ahmed, Xuan He, Jing Niu, Bin Zhou, Guangxiang Zhu, Tszshan Ma, Jiangpeikun Song, et al. “Integrating Hi-C and FISH data for modeling of the 3D organization of chromosomes.” Nature Communications 10 (2019): 2049.

9. Schuette, Greg, Zhuohan Lao, and Bin Zhang. “ChromoGen: Diffusion model predicts single-cell chromatin conformations.” Science Advances 11 (2025): eadr8265.

10. Bunne, Charlotte, Yusuf Roohani, Yanay Rosen, Ankit Gupta, Xikun Zhang, Marcel Roed, Theo Alexandrov, et al. “How to build the virtual cell with artificial intelligence: Priorities and opportunities.” Cell 187 (2024): 7045–7063.

11. Khan, Sumeer Ahmad, Xabier Martínez-de-Morentin, Abdel Rahman Alsabbagh, Alberto Maillo, Vincenzo Lagani, David Gomez-Cabrero, Robert Lehmann, and Jesper Tegner. “Multimodal foundation transformer models for multiscale genomics.” Nature Methods 23 (2026): 299–311.

12. Avsec, Žiga, Natasha Latysheva, Jun Cheng, Guido Novati, Kyle R. Taylor, Tom Ward, Clare Bycroft, et al. “Advancing regulatory variant effect prediction with AlphaGenome.” Nature 649 (2026): 1206–1218.

13. Ma, Mingqian, Yucheng Wu, Xin Chen, Feifei Jiang, Peijun Lin, Dongxin Ye, Yidi Sun, et al. “CENO: A genome-scale world model for evolutionary sequence interpretation and programmable regulatory design.” bioRxiv (2026).

14. “Norms and Distances.” BIOINF–MATH 540: Mathematics of Biological Networks, July 30, 2026.

15. Smith, Alexus A., Edmund L. Wong, Ronan C. Donovan, Brad A. Chapman, Ryan Harry, Pooyan Tirandazi, Paulina Kanigowska, et al. "Using a GPT-5-driven autonomous lab to optimize the cost and titer of cell-free protein synthesis." bioRxiv (2026).