References#

[AGB+25]

Abhinav K. Adduri, Dhruv Gautam, Beatrice Bevilacqua, Alishba Imran, Rohan Shah, Mohsen Naghipourfar, Noam Teyssier, and others. Predicting cellular responses to perturbation across diverse contexts with State. bioRxiv, 2025. STATE foundation model preprint. doi:10.1101/2025.06.26.661135.

[BiMVelezSB+22]

Pau Badia-i-Mompel, Jesús Vélez Santiago, Jana Braunger, and others. Decoupler: ensemble of computational methods to infer biological activities from omics data. Bioinformatics Advances, 2(1):vbac016, 2022.

[CHL+24]

Ang Cui, Teddy Huang, Shuqiang Li, and others. Dictionary of immune responses to cytokines at single-cell resolution. Nature, 625:377–384, 2024.

[CWM+24]

Haotian Cui, Chloe Wang, Hassaan Maan, and others. Scgpt: toward building a foundation model for single-cell multi-omics using generative ai. Nature Methods, 21:1470–1480, 2024.

[LRC+18]

Romain Lopez, Jeffrey Regier, Michael B. Cole, Michael I. Jordan, and Nir Yosef. Deep generative modeling for single-cell transcriptomics. Nature Methods, 15:1053–1058, 2018.

[SKKlunemann+18]

Michael Schubert, Bertram Klinger, Martina Klünemann, and others. Perturbation-response genes reveal signaling footprints in cancer gene expression. Nature Communications, 9:20, 2018.

[STM+05]

Aravind Subramanian, Pablo Tamayo, Vamsi K. Mootha, and others. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proceedings of the National Academy of Sciences, 102(43):15545–15550, 2005.

[SzekelyR13]

Gábor J. Székely and Maria L. Rizzo. Energy statistics: a class of statistics based on distances. Journal of Statistical Planning and Inference, 143(8):1249–1272, 2013.

[TureiVG+21]

Dénes Türei, Alberto Valdeolivas, Lejla Gul, and others. Integrated intra- and intercellular signaling knowledge for multicellular omics analysis. Molecular Systems Biology, 17(3):e9923, 2021.

[TXC+23]

Christina V. Theodoris, Ling Xiao, Anant Chopra, and others. Transfer learning enables predictions in network biology. Nature, 618:616–624, 2023.

[TIP+16]

Itay Tirosh, Benjamin Izar, Sanjay M. Prakadan, and others. Dissecting the multicellular ecosystem of metastatic melanoma by single-cell rna-seq. Science, 352(6282):189–196, 2016.

[WAT18]

F. Alexander Wolf, Philipp Angerer, and Fabian J. Theis. Scanpy: large-scale single-cell gene expression data analysis. Genome Biology, 19:15, 2018.