COVID-19 SARS-CoV-2 preprints from medRxiv and bioRxiv

30,580 Articles (22,415 medRxiv, 8,165 bioRxiv)

Most recent first Previous |  Page 36: Articles 351-360  | Next

Validation and Sensitivity Analysis of the COVID-19 Transmission Model Simulating Counterfactual Infections in Japan
Kakeya, H., Umeno, Y.
10.1101/2025.02.08.25321916 — Posted: 2025-02-14
Unraveling the Co-Morbidity between COVID-19 and Neurodegenerative Diseases Through Multi-scale Graph Analysis: A Systematic Investigation of Biological Databases and Text Mining
Babaiha, N. S., Geissler, S., Nibart, V., Atas Guevenilir, H., Bharadhwaj, V. S., Tom Kodamullil, A., Klein, J., Jacobs, M., Hofmann-Apitius, M.
10.1101/2025.02.13.637069 — Posted: 2025-02-14
SA55 broadly neutralizes SARS-CoV-2 and robustly prevents viral escape by JN.1 sublineages
Shi, L., Bowen, A., Han, J., Zheng, X., Luo, H., Yao, T., Guo, M., Yu, Y., Jian, F., Cao, Y. R., ke, l., Guo, Y., Liu, L.
10.1101/2025.02.12.638008 — Posted: 2025-02-14
Human type-I interferon omega holds potent antiviral properties and promotes cytolytic CD8+ T cell responses
Nguyen, H. O., Recordon-Pinson, P., Andreola, M.-L., Papagno, L., Appay, V.
10.1101/2025.02.13.638030 — Posted: 2025-02-14
Magnetoencephalography Reveals Neuroprotective Effects of COVID-19 Vaccination in Non-Human Primates
Stapleton-Kotloski, J., Rowland, J., Davenport, A., Epperly, P., Blevins, M., Godwin, D., Ewing, D., Liang, Z., Sundaram, A. K., Petrovsky, N., Porter, K., Gamble, C. S., Sanders, J. W., Daunais, J.
10.1101/2025.02.14.638187 — Posted: 2025-02-14
Design of Protein Sequences with Precisely Tuned Kinetic Properties
Brotzakis, Z. F., Vendruscolo, M., Skretas, G.
10.1101/2025.02.13.638027 — Posted: 2025-02-14
Developing Foundation Models for Predicting Viral Animal Host Range in Intelligent Surveillance
Guo, J., Guo, Q., Yin, H., Han, Y., Geng, P. X., Hou, J., Zhang, H., Tan, J., Li, M., Zhang, Y., Jiang, X., Zhu, H.
10.1101/2025.02.13.638012 — Posted: 2025-02-14
Identification of a multi-omics factor predictive of long COVID in the IMPACC study
Gabernet, G., Maciuch, J., Gygi, J. P., Moore, J. F., Hoch, A., Syphurs, C., Chu, T., Jayavelu, N. D., Corry, D. B., Kheradmand, F., Baden, L. R., Sekaly, R.-P., McComsey, G. A., Haddad, E. K., Cairns, C. B., Rouphael, N., Fernandez-Sesma, A., Simon, V., Metcalf, J. P., Agudelo Higuita, N. I., Hough, C. L., Messer, W. B., Davis, M. M., Nadeau, K. C., Pulendran, B., Kraft, M., Bime, C., Reed, E. F., Schaenman, J., Erle, D. J., Calfee, C. S., Atkinson, M. A., Brackenridge, S. C., Melamed, E., Shaw, A. C., Hafler, D. A., Ozonoff, A., Bosinger, S. E., Eckalbar, W., Maecker, H. T., Kim-Schulze, S., Steen, H., Krammer, F., Westendorf, K., IMPACC Network, , Peters, B., Fourati, S., Altman, M. C., Levy, O., Smolen, K. K., Montgomery, R. R., Diray-Arce, J., Kleinstein, S. H., Guan, L., Ehrlich, L. I. R.
10.1101/2025.02.12.637926 — Posted: 2025-02-14
A Machine-Learning Approach to Finding Gene Target Treatment Options for Long COVID
Lopez-Rincon, A.
10.1101/2025.02.07.25321856 — Posted: 2025-02-13
Machine learning models predict long COVID outcomes based on baseline clinical and immunologic factors
Jayavelu, N. D., Samaha, H., Wimalasena, S. T., Hoch, A., Gygi, J. P., Gabernet, G., Ozonoff, A., Liu, S., Milliren, C. E., Levy, O., Baden, L. R., Melamed, E., Ehrlich, L. I. R., McComsey, G. A., Sekaly, R. P., Cairns, C. B., Haddad, E. K., Schaenman, J., Shaw, A. C., Hafler, D. A., Montgomery, R. R., Corry, D. B., Kheradmand, F., Atkinson, M. A., Brakenridge, S. C., Higuita, N. I. A., Metcalf, J. P., Hough, C. L., Messer, W. B., Pulendran, B., Nadeau, K. C., Davis, M. M., Geng, L. N., Sesma, A. F., Simon, V., Krammer, F., Kraft, M., Bime, C., Calfee, C. S., Erle, D. J., Langelier, C. R., IMP
10.1101/2025.02.12.25322164 — Posted: 2025-02-13

RSS  Collection RSS | JSON

The feeds linked above output metadata for the 100 most recent papers in the collection.To access the metadata for the entire collection in JSON or XML, visit the collection API.

Subject Areas
* The Clinical Trials and Epidemiology subject categories are now closed to new submissions following the completion of bioRxiv's clinical research pilot project and launch of the dedicated health sciences server medRxiv (submit.medrxiv.org). New papers that report results of Clinical Trials must now be submitted to medRxiv. Most new Epidemiology papers also should be submitted to medRxiv, but if a paper contains no health-related information, authors may choose to submit it to another bioRxiv subject category (e.g., Genetics or Microbiology).