Our fellows publish foundational advances in machine learning and new computational methods for biology in leading journals — and present their work at conferences around the world.
Gangrade, A., Pacchiano, A., Scott, C., & Saligrama, V.
(
2025
).
Feasible Action Search for Bandit Linear Programs via Thompson Sampling.
Forty-Second International Conference on Machine Learning (ICML 2025)
,
(
).
https://icml.cc/virtual/2025/poster/45807Russo, A., & Pacchiano, A.
(
2025
).
Adaptive Exploration for Multi-Reward Multi-Policy Evaluation.
Forty-Second International Conference on Machine Learning (ICML 2025)
,
(
).
https://doi.org/10.48550/arXiv.2502.02516German, J., Yang, Z., Urbut, S., Vartiainen, P., FinnGen, Natarajan, P., Pattorno, E., Kutalik, Z., Philippakis, A., & Ganna, A.
(
2025
).
Incorporating genetic data improves target trial emulations and informs the use of polygenic scores in randomized controlled trial design
Nature Genetics
,
(
).
https://www.nature.com/articles/s41588-025-02229-8Tonekaboni, S., Behrouzi, T., Weatherhead, A., Fox, E., Blei, D., & Goldenberg, A.
(
2025
).
HDP-Flow: Generalizable Bayesian Nonparametric Model for Time Series State Discovery.
The 41st Conference on Uncertainty in Artificial Intelligence.
,
(
).
https://openreview.net/forum?id=Ti1TMJiprQ&referrer=%5Bthe%20profile%20of%20Emily%20Fox%5D(%2Fprofile%3Fid%3D~Emily_Fox2)Hu, X., & Pacchiano, A.
(
2025
).
Meet Me at the Arm: The Cooperative Multi-Armed Bandits Problem with Shareable Arms.
arXiv [Preprint]
,
(
).
https://doi.org/10.48550/arXiv.2506.10127Hulland, E. N., Charpignon, M.-L., Berkane, T., & Majumder, M. S.
(
2025
).
Underimmunisation during the 2025 Texas measles outbreak.
The Lancet Infectious Diseases
,
25
(
6
).
Samarah, L. Z., Zheng, C., Xing, X., Lee, W. D., Afriat, A., Chitra, U., MacArthur, M., Lu, W., Jankowski, C. S. R., Ma, C., Hunter, C. J., Raphael, B. J., & Rabinowitz, J. D.
(
2025
).
Spatial metabolic gradients in the liver and small intestine.
bioRxiv [Preprint]
,
(
).
https://www.biorxiv.org/content/10.1101/2025.06.02.657306v1Russo, A., Welch, R., & Pacchiano, A.
(
2025
).
Learning to Explore: An In-Context Learning Approach for Pure Exploration.
arXiv [Preprint]
,
(
).
https://doi.org/10.48550/arXiv.2506.01876Turura, Y., Friedman, S. F., Cremer, A., Maddah, M., & Tonekaboni, S.
(
2025
).
The Latentverse: An Open-Source Benchmarking Toolkit for Evaluating Latent Representations.
Conference on Health, Inference, and Learning (CHIL 2025)
,
(
).
https://doi.org/10.1101/2025.04.25.650676Brukhim, N., Pacchiano, A., Dudik, M., & Schapire, R.
(
2025
).
On the Hardness of Bandit Learning.
Conference on Learning Theory (COLT 2025)
,
(
).
https://doi.org/10.48550/arXiv.2506.14746Ost, L., Montesano, S. C. di, & Edelsbrunner, H.
(
2025
).
Banana Trees for the Persistence in Time Series Experimentally.
The 41st International Symposium on Computational Geometry (SoCG 2025)
,
(
).
https://doi.org/10.48550/arXiv.2405.17920Yin, L., Lin, Y., Qiu, J., Xiang, Y., Li, M., Xiao, X., Lui, S. S.-Y., & So, H.-C.
(
2025
).
Integrating brain imaging features and genomic profiles for the subtyping of major depression.
Psychological Medicine
,
55
(
e158
).
https://doi.org/10.1017/S0033291725001096Zhang, X., Tseo, Y., Bai, Y., Chen, F., & Uhler, C.
(
2025
).
Prediction of protein subcellular localization in single cells.
Nature Methods
,
22
(
6
).
https://www.nature.com/articles/s41592-025-02696-1Mazaheri, B., Jain, S., Cook, M., & Bruck, J.
(
2025
).
Omitted Labels in Causality: A Study of Paradoxes.
CLeaR (Causal Learning and Reasoning) 2025
,
(
).
https://doi.org/10.48550/arXiv.2311.06840Xu, W., Wu, Q., Liang, Z., Han, J., Ning, X., Shi, Y., Lin, W., & Zhang, Y.
(
2025
).
SLMRec: Distilling Large Language Models into Small for Sequential Recommendation.
The Thirteenth International Conference on Learning Representations (ICLR 2025)
,
(
).
https://doi.org/10.48550/arXiv.2405.17890Russo, A., Song, Y., & Pacchiano, A.
(
2025
).
Pure Exploration with Feedback Graphs.
The 28th International Conference on Artificial Intelligence and Statistics (AISTATS 2025)
,
(
).
https://openreview.net/forum?id=ybpHHnBf7xMazaheri, B., Squires, C., & Uhler, C.
(
2025
).
Synthetic Potential Outcomes and Causal Mixture Identifiability.
The 28th International Conference on Artificial Intelligence and Statistics (AISTATS 2025)
,
(
).
https://openreview.net/forum?id=J1CJaSnmKg&referrer=%5Bthe%20profile%20of%20Caroline%20Uhler%5D(%2Fprofile%3Fid%3D~Caroline_Uhler1Pourmousa, M., Jain, S., Barnaeva, E., Jin, W., Hochuli, J., Itkin, Z., Maxfield, T., Melo-Filho, C., Thieme, A., Wilson, K., Klumpp-Thomas, C., Michael, S., Southall, N., Jaakkola, T., Muratov, E. N., Barzilay, R., Tropsha, A., Ferrer, M., & Zakharov, A. V.
(
2025
).
AI-driven discovery of synergistic drug combinations against pancreatic cancer.
Nature Communications
,
16
(
1
).
https://www.nature.com/articles/s41467-025-56818-6German, J., Cordioli, M., Tozzo, V., Urbut, S., Arumäe, K., Smit, R. A. J., Lee, J., Li, J. H., Janucik, A., Ding, Y., Akinkuolie, A., Heyne, H., Eoli, A., Saad, C., Al-Sarraj, Y., Abdel-latif, R., Barry, A., Wang, Z., Team, E. B. research, … Ganna, A.
(
2025
).
Association between plausible genetic factors and weight loss from GLP1-RA and bariatric surgery: A multi-ancestry study in 10,960 individuals from 9 biobanks.
Nature Medicine
,
(
).
https://pubmed.ncbi.nlm.nih.gov/40251273/A. Radhakrishnan,M. Belkin,& D. Drusvyatskiy
(
2025
).
Linear Recursive Feature Machines provably recover low-rank matrices
Proceedings of the National Academy of Sciences (PNAS)
,
122
(
13
).
https://www.pnas.org/doi/10.1073/pnas.2411325122Nagaraj, S., Gerych, W., Tonekaboni, S., Goldenberg, A., Ustun, B., & Hartvigsen, T.
(
2025
).
Learning Under Temporal Label Noise.
The Thirteenth International Conference on Learning Representations (ICLR 2025)
,
(
).
https://openreview.net/pdf?id=5o0phqAhsPWang, C., Gupta, S., Zhang, X., Tonekaboni, S., Jegelka, S., Jaakkola, T., & Uhler, C.
(
2025
).
An Information Criterion for Controlled Disentanglement of Multimodal Data
The Thirteenth International Conference on Learning Representations (ICLR 2025)
,
(
).
https://openreview.net/pdf?id=3n4RY25UWPZhang, H., Fang, L., Wu, Q., & Yu, P. S.
(
2025
).
DiffPuter: An EM-Driven Diffusion Model for Missing Data Imputation.
The Thirteenth International Conference on Learning Representations (ICLR 2025)
,
(
).
https://openreview.net/forum?id=3fl1SENSYOZhang, C. B. C., Hong, Z.-W., Pacchiano, A., & Agrawal, P.
(
2025
).
ORSO: Accelerating Reward Design via Online Reward Selection and Policy Optimization.
The Thirteenth International Conference on Learning Representations (ICLR 2025)
,
(
).
https://arxiv.org/abs/2410.13837Kausik, C., Mutti, M., Pacchiano, A., & Tewari, A.
(
2025
).
A Theoretical Framework for Partially-Observed Reward States in RLHF.
The Thirteenth International Conference on Learning Representations (ICLR 2025)
,
(
).
https://openreview.net/forum?id=OjAU0LLDbeChen, Y., Wu, Q., & Yan, J.
(
2025
).
Regularizing Energy among Training Samples for Out-of-Distribution Generalization.
The Thirteenth International Conference on Learning Representations (ICLR 2025)
,
(
).
https://openreview.net/forum?id=Lbx9zdURxePacchiano, A.
(
2025
).
Second Order Bounds for Contextual Bandits with Function Approximation.
The Thirteenth International Conference on Learning Representations (ICLR 2025)
,
(
).
https://openreview.net/forum?id=h6ktwCPYxEBerliner Senderey, A., Mushkat, T., Hadass, O., Carmeli, D., Hayek, S., Charpingnon, M.-L., Jacobson, E., & Balicer, R. D.
(
2025
).
Real-world impact of physical activity reward-driven digital app use on cardiometabolic and cardiovascular disease incidence.
Communications Medicine,
,
5
(
1
).
https://doi.org/10.1038/s43856-025-00792-zShankar, P., Liang, H., Chitra, U., & Singh, R.
(
2025
).
Decoding the causal drivers of spatial cellular topology.
bioRxiv [Preprint]
,
(
).
https://www.biorxiv.org/content/10.1101/2025.03.19.644241v2Fischer, D. S., Villanueva, M. A., Winter, P. S., & Shalek, A. K.
(
2025
).
Adapting systems biology to address the complexity of human disease in the single-cell era.
Nature Reviews Genetics
,
(
).
https://www.nature.com/articles/s41576-025-00821-6Shenfeld, I., Faltings, F., Agrawal, P., & Pacchiano, A.
(
2025
).
Language Model Personalization via Reward Factorization.
arXiv [Preprint]
,
(
).
https://doi.org/10.48550/arXiv.2503.06358Barabási, D. L., Ferreira Castro, A., & Engert, F.
(
2025
).
Three systems of circuit formation: Assembly, updating and tuning.
Nature Reviews Neuroscience
,
26
(
4
).
https://www.nature.com/articles/s41583-025-00910-9Parres-Gold, J., Levine, M., Emert, B., Stuart, A., & Elowitz, M. B.
(
2025
).
Contextual computation by competitive protein dimerization networks.
Cell
,
188
(
).
https://www.cell.com/cell/fulltext/S0092-8674(25)00105-9Chitra, U., Arnold, B., & Raphael, B. J.
(
2025
).
Resolving discrepancies between chimeric and multiplicative measures of higher-order epistasis.
Nature Communications
,
16
(
1
).
https://www.nature.com/articles/s41467-025-56986-5Najia, M. A., Jha, D. K., Zhang, C., Laurent, B., Kubaczka, C., Markel, A., Li, C., Morris, V., Tompkins, A., Hensch, L., Qin, Y., Chapuy, B., Huang, Y.-C., Morse, M., Marunde, M. R., Vaidya, A., Gillespie, Z. B., Howard, S. A., North, T. E., … Daley, G. Q.
(
2025
).
Heterochromatin fidelity is a therapeutic vulnerability in lymphoma and other human cancers.
bioRxiv [Preprint]
,
(
).
https://pubmed.ncbi.nlm.nih.gov/39975048/Najia, M. A., Jha, D. K., Zhang, C., Laurent, B., Kubaczka, C., Markel, A., Li, C., Morris, V., Tompkins, A., Hensch, L., Qin, Y., Chapuy, B., Huang, Y.-C., Morse, M., Marunde, M. R., Vaidya, A., Gillespie, Z. B., Howard, S. A., North, T. E., … Daley, G. Q.
(
2025
).
Heterochromatin fidelity is a therapeutic vulnerability in lymphoma and other human cancers.
bioRxiv [Preprint]
,
(
).
https://www.biorxiv.org/content/10.1101/2025.01.31.635709v1Chitra, U., Dan, S., Krienen, F., & Raphael, B. J.
(
2025
).
GASTON-Mix: A unified model of spatial gradients and domains using spatial mixture-of-experts.
bioRxiv [Preprint]
,
(
).
https://www.biorxiv.org/content/10.1101/2025.01.31.635955v1Schuster, V.
(
2025
).
Can sparse autoencoders make sense of latent representations?
arXiv [Preprint]
,
(
).
https://doi.org/10.48550/arXiv.2410.11468Kovačević, L., Gaudelet, T., Opzoomer, J., Triendl, H., Whittaker, J., Uhler, C., Edwards, L., & Taylor-King, J. P.
(
2025
).
No Foundations without Foundations—Why semi-mechanistic models are essential for regulatory biology.
arXiv [Preprint]
,
(
).
https://doi.org/10.48550/arXiv.2501.19178Schlüter, H. M., & Uhler, C.
(
2025
).
Integrating representation learning, permutation, and optimization to detect lineage-related gene expression patterns.
Nature Communications
,
16
(
1
).
https://www.nature.com/articles/s41467-025-56388-7Chitra, U., Arnold, B. J., Sarkar, H., Ma, C., Lopez-Darwin, S., Sanno, K., & Raphael, B. J.
(
2025
).
Mapping the topography of spatial gene expression with interpretable deep learning.
Nature Methods
,
22, 298–309
(
).
https://doi.org/10.1038/s41592-024-02503-3Lalchand, V., & Eilers, A.-C
(
2025
).
Shared Stochastic Gaussian Process Latent Variable Models: A Multi-modal Generative Model for Quasar Spectra.
Transactions on Machine Learning Research (TMLR 2025)
,
(
).
Charpignon, M.-L., Matos, J., Nakayama, L. F., Gallifant, J., Alfonso, P. G. I., Cobanaj, M., Fiske, A. M., Gates, A. J., Ho, F. D. V., Jain, U., Kashkooli, M., Link, N., McCoy, L. G., Shaffer, J., & Celi, L. A.
(
2025
).
Diversity in the medical research ecosystem: A descriptive scientometric analysis of over 49,000 studies and 150,000 authors published in high-impact medical journals between 2007 and 2022.
BMJ Open
,
15
(
1
).
https://bmjopen.bmj.com/content/15/1/e086982Gentili, M., Carlson, R. J., Liu, B., Hellier, Q., Andrews, J., Qin, Y., Blainey, P. C., & Hacohen, N.
(
2024
).
Classification and functional characterization of regulators of intracellular STING trafficking identified by genome-wide optical pooled screening.
Cell Systems
,
15
(
12
).
https://www.cell.com/cell-systems/abstract/S2405-4712(24)00337-5Kumar, A., Shiragur, K., & Uhler, C.
(
2024
).
Learning Mixtures of Unknown Causal Interventions.
Advances in Neural Information Processing Systems (NeurIPS 2024)
,
37
(
).
https://proceedings.neurips.cc/paper_files/paper/2024/hash/1dcee1cd6890ab7fcdf173ec10526da9-Abstract-Conference.htmlBarlow, G. L., Schürch, C. M., Bhate, S. S., Phillips, D., Young, A., Dong, S., Martinez, H. A., Kaber, G., Nagy, N., Ramachandran, S., Meng, J., Korpos, E., Bluestone, J. A., Nolan, G. P., & Bollyky, P. L.
(
2024
).
The Extra-Islet Pancreas Supports Autoimmunity in Human Type 1 Diabetes.
medRxiv [Preprint]
,
(
).
https://pubmed.ncbi.nlm.nih.gov/36993739/Welch, R., Zhang, J., & Uhler, C.
(
2024
).
Identifiability Guarantees for Causal Disentanglement from Purely Observational Data.
The Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS 2024)
,
(
).
https://neurips.cc/virtual/2024/poster/95550Baharav, T., Kang, R., Sullivan, C., Tiwari, M., Luxenberg, E., Tse, D., & Pilanci, M.
(
2024
).
Adaptive Sampling for Efficient Softmax Approximation.
Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS 2024)
,
(
).
https://nips.cc/virtual/2024/poster/94739Garcia, C. C., Venkat, A., McQuaid, D. C., Agabiti, S., Tong, A., Cardone, R. L., Starble, R., Sogunro, A., Jacox, J. B., Ruiz, C. F., Kibbey, R. G., Krishnaswamy, S., & Muzumdar, M. D.
(
2024
).
Beta cells are essential drivers of pancreatic ductal adenocarcinoma development.
bioRxiv [Preprint]
,
(
).
https://www.biorxiv.org/content/10.1101/2024.11.29.626079v1Sornapudi, T. R., Yuan, L., Braunger, J. M., Uhler, C., & Shivashankar, G. V.
(
2024
).
Remodeling of cytoskeleton, chromatin, and gene expression during mechanical rejuvenation of aged human dermal fibroblasts.
Molecular Biology of the Cell
,
36
(
1
).
https://www.molbiolcell.org/doi/10.1091/mbc.E24-09-0430Venkat, A., Leone, S., Youlten, S. E., Fagerberg, E., Attanasio, J., Joshi, N. S., Perlmutter, M., & Krishnaswamy, S.
(
2024
).
Mapping the gene space at single-cell resolution with gene signal pattern analysis.
Nature Computational Science
,
4
(
12
).
https://www.nature.com/articles/s43588-024-00734-0Gupta, R., Goswami, Y., Yuan, L., Roy, B., Pereiro, E., & Shivashankar, G. V.
(
2024
).
Correlative light and soft X-ray tomography of in situ mesoscale heterochromatin structure in intact cells.
Scientific Reports
,
14
(
1
).
https://doi.org/10.1038/s41598-024-77361-2Rahimov, F., Nieminen, P., Kumari, P., Juuri, E., Nikopensius, T., Paraiso, K., German, J., Karvanen, A., Kals, M., Elnahas, A. G., Karjalainen, J., Kurki, M., Palotie, A., Heliövaara, A., Esko, T., Jukarainen, S., Palta, P., Ganna, A., Patni, A. P., … Rice, D. P.
(
2024
).
High incidence and geographic distribution of cleft palate in Finland are associated with the IRF6 gene.
Nature Communications
,
15
(
1
).
https://www.nature.com/articles/s41467-024-53634-2Huang, T., Song, Z., Ying, R., & Jin, W.
(
2024
).
Protein-Nucleic Acid Complex Modeling with Frame Averaging Transformer.
arXiv [Preprint]
,
(
).
http://arxiv.org/abs/2406.09586Abedsoltan, A., Radhakrishnan, A., Wu, J., & Belkin, M.
(
2024
).
Context-Scaling versus Task-Scaling in In-Context Learning.
arXiv [Preprint]
,
(
).
http://arxiv.org/abs/2410.12783Zhang, X., Shivashankar, G. V., & Uhler, C.
(
2024
).
Partially Shared Multi-Modal Embedding Learns Holistic Representation of Cell State.
bioRxiv [Preprint]
,
(
).
https://www.biorxiv.org/content/10.1101/2024.10.01.615977v1Matos, J., Gallifant, J., Chowdhury, A., Economou-Zavlanos, N., Charpignon, M.-L., Gichoya, J., Celi, L. A., Nazer, L., King, H., & Wong, A.-K. I.
(
2024
).
A Clinician’s Guide to Understanding Bias in Critical Clinical Prediction Models.
Critical Care Clinics
,
40
(
4
).
https://doi.org/10.1016/j.ccc.2024.05.011Chen, M., Pacchiano, A., & Zhang, X.
(
2024
).
State-free Reinforcement Learning.
Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS 2024)
,
(
).
https://doi.org/10.48550/arXiv.2409.18439Sikdar, S., Venturini, S., Charpignon, M.-L., Kumar, S., Rinaldi, F., Tudisco, F., Fortunato, S., & Majumder, M. S.
(
2024
).
What we should learn from pandemic publishing.
Nature Human Behaviour
,
8
(
9
).
https://www.nature.com/articles/s41562-024-01969-7Anagnostou, E., Kouvli, M., Karagianni, E., Gamvroula, A., Kalamatianos, T., Stranjalis, G., & Skoularidou, M.
(
2024
).
Romberg’s test revisited: Changes in classical and advanced sway metrics in patients with pure sensory neuropathy.
Neurophysiologie Clinique
,
54
(
5
).
https://pubmed.ncbi.nlm.nih.gov/39042993/Rodríguez, A., Adhikari, B., Srivastava, A., Pei, S., Charpignon, M.-L., Wang, K., Chang, S., Vullikanti, A., & Prakash, B. A.
(
2024
).
epiDAMIK 2024: The Seventh International Workshop on Epidemiology meets Data Mining and Knowledge Discovery.
KDD '24: The Thirtieth ACM SIGKDD Conference on Knowledge Discovery and Data Mining
,
(
).
https://dl.acm.org/doi/10.1145/3637528.3671480Hulland, E. N., Charpignon, M.-L., Hayek, G. Y. E., Zhao, L., Desai, A. N., & Majumder, M. S.
(
2024
).
Estimating time-varying transmission and oral cholera vaccine effectiveness in Haiti and Cameroon, 2021-2023.
medRxiv [Preprint]
,
(
).
Montesano, S. C. di, Draganov, O., Edelsbrunner, H., & Saghafian, M.
(
2024
).
The Euclidean MST-ratio for Bi-colored Lattices.
arXiv [Preprint]
,
(
).
https://arxiv.org/abs/2403.10204Kokot, M., Dehghannasiri, R., Baharav, T., Salzman, J., & Deorowicz, S.
(
2024
).
Scalable and unsupervised discovery from raw sequencing reads using SPLASH2.
Nature Biotechnology
,
(
).
https://doi.org/10.1038/s41587-024-02381-2Rodríguez, A., Adhikari, B., Srivastava, A., Pei, S., Charpignon, M.-L., Wang, K., Chang, S., Vullikanti, A., & Prakash, B.A
(
2024
).
epiDAMIK 2024: The 7th International Workshop on Epidemiology meets Data Mining and Knowledge Discovery.
KDD '24: Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
,
(
).
Mallinar, N., Beaglehole, D., Zhu, L., Radhakrishnan, A., Pandit, P., & Belkin, M.
(
2024
).
Emergence in non-neural models: Grokking modular arithmetic via average gradient outer product.
arXiv [Preprint]
,
(
).
https://doi.org/10.48550/arXiv.2407.20199McGee, E. M., García de Albéniz, X., Eliassen, H., Yim, K., Dickerman, B., Preston, M., & Hernán, M.
(
2024
).
Target trial emulation of dynamic surveillance strategies for cancer survivors: An application to non-muscle invasive bladder cancer.
Society for Epidemiologic Research (SER) Annual Meeting
,
(
).
Charpignon, M.-L., Celi, L. A., Cobanaj, M., Eber, R., Fiske, A., Gallifant, J., Li, C., Lingamallu, G., Petushkov, A., & Pierce, R.
(
2024
).
Diversity and inclusion: A hidden additional benefit of Open Data.
PLOS Digital Health
,
3
(
7
).
https://journals.plos.org/digitalhealth/article?id=10.1371/journal.pdig.0000486Zou, B. J., Levine, M. E., Zaharieva, D. P., Johari, R., & Fox, E.
(
2024
).
Hybrid Squared Neural ODE Causal Modeling and an Application to Glycemic Response.
Proceedings of the Forty-First International Conference on Machine Learning
,
PMLR 235:62934-62963
(
).
https://proceedings.mlr.press/v235/zou24b.htmlSong, Z., Zhao, Y., Shi, W., Jin, W., Yang, Y., & Li, L.
(
2024
).
Generative enzyme design guided by functionally important sites and small-molecule substrates.
41st International Conference on Machine Learning (ICML 2024)
,
PMLR 235
(
).
https://openreview.net/pdf/b349f5504ef1e6143231064979e2e96feaf5a6a9.pdfZhang, X., Venkatachalapathy, S., Paysan, D., Schaerer, P., Tripodo, C., Uhler, C., & Shivashankar, G. V.
(
2024
).
Unsupervised representation learning of chromatin images identifies changes in cell state and tissue organization in DCIS.
Nature Communications
,
15
(
1
).
https://www.nature.com/articles/s41467-024-50285-1Chitra, U., Arnold, B. J., & Raphael, B. J.
(
2024
).
Quantifying higher-order epistasis: Beware the chimera.
bioRxiv [Preprint]
,
(
).
https://www.biorxiv.org/content/10.1101/2024.07.17.603976v1Song, Z., Huang, T., Li, L., & Jin, W.
(
2024
).
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