Zhang, R., Tai, J., Yao, Q., Yang, W., Ruggeri, K., Shaman, J., & Pei, S. (2025). Behavior-driven forecasts of neighborhood-level COVID-19 spread in New York City. PLOS Computational Biology, 21(4), e1012979. https://doi.org/10.1371/journal.pcbi.1012979

Dinh, K. N., Vázquez-García, I., Chan, A., Malhotra, R., Weiner, A., McPherson, A. W., & Tavaré, S. (2025). CINner: Modeling and simulation of chromosomal instability in cancer at single-cell resolution. PLOS Computational Biology, 21(4), e1012902. https://doi.org/10.1371/journal.pcbi.1012902

Yao, Y., Pauls, S., Foley, D., Yoshikawa, T., Honma, S., Honma, K.-I., McVeigh, E., Foley, N. C., & Silver, R. (2025). Suprachiasmatic nucleus-wide estimation of oscillatory temporal dynamics. PLOS Computational Biology, 21(3), e1012855. https://doi.org/10.1371/journal.pcbi.1012855

Saad-Roy, C. M., Morris, S. E., Boots, M., Baker, R. E., Lewis, B. L., Farrar, J., Marathe, M. V., Graham, A. L., Levin, S. A., Wagner, C. E., Metcalf, C. J. E., & Grenfell, B. T. (2024). Impact of waning immunity against SARS-CoV-2 severity exacerbated by vaccine hesitancy. PLOS Computational Biology, 20(8), e1012211. https://doi.org/10.1371/journal.pcbi.1012211

Holt, C. J., Miller, K. D., & Ahmadian, Y. (2024). The stabilized supralinear network accounts for the contrast dependence of visual cortical gamma oscillations. PLOS Computational Biology, 20(6), e1012190. https://doi.org/10.1371/journal.pcbi.1012190

Lopez, V. K., Cramer, E. Y., Pagano, R., Drake, J. M., O’Dea, E. B., Adee, M., Ayer, T., Chhatwal, J., Dalgic, O. O., Ladd, M. A., Linas, B. P., Mueller, P. P., Xiao, J., Bracher, J., Castro Rivadeneira, A. J., Gerding, A., Gneiting, T., Huang, Y., Jayawardena, D., … Johansson, M. A. (2024). Challenges of COVID-19 Case Forecasting in the US, 2020–2021. PLOS Computational Biology, 20(5), e1011200. https://doi.org/10.1371/journal.pcbi.1011200

Kay, K., Biderman, N., Khajeh, R., Beiran, M., Cueva, C. J., Shohamy, D., Jensen, G., Wei, X.-X., Ferrera, V. P., & Abbott, L. (2024). Emergent neural dynamics and geometry for generalization in a transitive inference task. PLOS Computational Biology, 20(4), e1011954. https://doi.org/10.1371/journal.pcbi.1011954

van Boven, M., van Dorp, C. H., Westerhof, I., Jaddoe, V., Heuvelman, V., Duijts, L., Fourie, E., Sluiter-Post, J., van Houten, M. A., Badoux, P., Euser, S., Herpers, B., Eggink, D., de Hoog, M., Boom, T., Wildenbeest, J., Bont, L., Rozhnova, G., Bonten, M. J., … Bruijning-Verhagen, P. (2024). Estimation of introduction and transmission rates of SARS-CoV-2 in a prospective household study. PLOS Computational Biology, 20(1), e1011832. https://doi.org/10.1371/journal.pcbi.1011832

Zhao, H., Wu, H., Guseman, A., Abeykoon, D., Camara, C. M., Dalal, Y., Fushman, D., & Papoian, G. A. (2024). The role of cryptic ancestral symmetry in histone folding mechanisms across Eukarya and Archaea. PLOS Computational Biology, 20(1), e1011721. https://doi.org/10.1371/journal.pcbi.1011721

Cascante-Vega, J., Galanti, M., Schley, K., Pei, S., & Shaman, J. (2023). Inference of transmission dynamics and retrospective forecast of invasive meningococcal disease. PLOS Computational Biology, 19(10), e1011564. https://doi.org/10.1371/journal.pcbi.1011564

Zhang, R., Tai, J., & Pei, S. (2023). Ensemble inference of unobserved infections in networks using partial observations. PLOS Computational Biology, 19(8), e1011355. https://doi.org/10.1371/journal.pcbi.1011355

Yang, W., & Shaman, J. (2023). Development of Accurate Long-lead COVID-19 Forecast. PLOS Computational Biology, 19(7), e1011278. https://doi.org/10.1371/journal.pcbi.1011278

Kandula, S., Olfson, M., Gould, M. S., Keyes, K. M., & Shaman, J. (2023). Hindcasts and forecasts of suicide mortality in US: A modeling study. PLOS Computational Biology, 19(3), e1010945. https://doi.org/10.1371/journal.pcbi.1010945

Ashinoff, B. K., Buck, J., Woodford, M., & Horga, G. (2022). The effects of base rate neglect on sequential belief updating and real-world beliefs. PLOS Computational Biology, 18(12), e1010796. https://doi.org/10.1371/journal.pcbi.1010796

Malina, S., Cizin, D., & Knowles, D. A. (2022). Deep mendelian randomization: Investigating the causal knowledge of genomic deep learning models. PLOS Computational Biology, 18(10), e1009880. https://doi.org/10.1371/journal.pcbi.1009880

Chen, Y., Liu, T., Yu, X., Zeng, Q., Cai, Z., Wu, H., Zhang, Q., Xiao, J., Ma, W., Pei, S., & Guo, P. (2022). An ensemble forecast system for tracking dynamics of dengue outbreaks and its validation in China. PLOS Computational Biology, 18(6), e1010218. https://doi.org/10.1371/journal.pcbi.1010218

Schneider, T., Dunbar, O. R. A., Wu, J., Böttcher, L., Burov, D., Garbuno-Inigo, A., Wagner, G. L., Pei, S., Daraio, C., Ferrari, R., & Shaman, J. (2022). Epidemic management and control through risk-dependent individual contact interventions. PLOS Computational Biology, 18(6), e1010171. https://doi.org/10.1371/journal.pcbi.1010171

Ukawuba, I., & Shaman, J. (2022). Inference and dynamic simulation of malaria using a simple climate-driven entomological model of malaria transmission. PLOS Computational Biology, 18(6), e1010161. https://doi.org/10.1371/journal.pcbi.1010161

Chen, S., Loper, J., Zhou, P., & Paninski, L. (2022). Blind demixing methods for recovering dense neuronal morphology from barcode imaging data. PLOS Computational Biology, 18(4), e1009991. https://doi.org/10.1371/journal.pcbi.1009991

Zelner, J., Masters, N. B., Naraharisetti, R., Mojola, S. A., Chowkwanyun, M., & Malosh, R. (2022). There are no equal opportunity infectors: Epidemiological modelers must rethink our approach to inequality in infection risk. PLOS Computational Biology, 18(2), e1009795. https://doi.org/10.1371/journal.pcbi.1009795