Papers

2024

Wang, X., Tan, W., Martinez, K., McMahon, B. H., Beckham, J. C., Kimbrel, N. A., & Crivelli, S. (2024). Association between social and environmental determinants of health with suicide-related death among veterans. medRxiv, 2024-07. 10.1101/2024.07.02.24309854
Zamora-Resendiz, R., Khurram, I., & Crivelli, S. (2024). Towards Maps of Disease Progression: Biomedical Large Language Model Latent Spaces For Representing Disease Phenotypes And Pseudotime. medRxiv, 2024-06. doi.org/10.1101/2024.06.16.24308979
Bryant, A. K., Zamora‐Resendiz, R., Dai, X., Morrow, D., Lin, Y., Jungles, K. M., ... & Green, M. D. (2024). Artificial intelligence to unlock real‐world evidence in clinical oncology: A primer on recent advances. Cancer medicine, 13(12), e7253. doi.org/10.1002/cam4.7253
Ahmed, A., Rispoli, A., Wasieloski, C., Khurram, I., Zamora-Resendiz, R., Morrow, D., ... & Crivelli, S. (2024). Predictive Modeling and Deep Phenotyping of Obstructive Sleep Apnea and Associated Comorbidities through Natural Language Processing and Large Language Models. medRxiv, 2024-04. doi.org/10.1101/2024.04.19.24306084
Martinez, C., Levin, D., Jones, J., Finley, P. D., McMahon, B., Dhaubhadel, S., ... & Beckham, J. C. (2024). Deep sequential neural network models improve stratification of suicide attempt risk among US veterans. Journal of the American Medical Informatics Association, 31(1), 220-230. doi.org/10.1093/jamia/ocad167

N.A. Kimbrel, A.E. Ashley-Koch, X.J. Qin, et al. (2023). “Identification of Novel, Replicable Genetic Risk Loci for Suicidal Thoughts and Behaviors Among US Military Veterans.” JAMA Psychiatry. 2023;80(2):135–145. DOI:10.1001/jamapsychiatry.2022.3896

R.T. Payne, S. Crivelli, M. Watanabe (2022). “All-Atom Simulations Uncover Structural and Dynamical Properties of STING Proteins in the Membrane System.” J of Chem Inf and Model. 2022 62 (18), 4486-4499. DOI: 10.1021/acs.jcim.2c00595.
X. Wang, R. Zamora-Resendiz, C.D. Shelley, C. Manore, X. Liu, D.W. Oslin, B. McMahon, J.C. Beckham, N.A. Kimbrel, S. Crivelli (2022). “An examination of the association between altitude and suicide deaths, suicide attempts, and suicidal ideation among veterans at both the patient and geospatial level.” J Psychiatr Res. Vol. 153, 2022, 276-283, ISSN 0022-3956, https://doi.org/10.1016/j.jpsychires.2022.07.017.
D. Morrow, R. Zamora-Resendiz, J.C. Beckham, N.A. Kimbrel, D.W. Oslin, S. Tamang, S. Crivelli (2022). “A case for developing domain-specific vocabularies for extracting suicide factors from healthcare notes.” J Psychiatr Res. Vol. 151, 2022, 328-338, ISSN 0022-3956, https://doi.org/10.1016/j.jpsychires.2022.04.009.
Crivelli, S., Wang, X., Brusco, B., Tan, W., Beckham, J. and Kimbrel, N. (2022) Association Between Social and Environmental Determinants of Health and Suicide Rates for the US Population. In Fall Meeting 2022. AGU.

E.A. Lubecka, A.S. Karczyńska, A.G. Lipska, A.K. Sieradzan, K. Ziȩba, C. Sikorska, U. Uciechowska, S.A. Samsonov, P. Krupa, M.A. Mozolewska, Ł. Golon, A. Giełdoń, C. Czaplewski, R. Ślusarz, M. Ślusarz, S.N. Crivelli, A. Liwo (2019). "Evaluation of the scale-consistent UNRES force field in template-free prediction of protein structures in the CASP13 experiment." J Mol Graph Model. Nov 2019;92:154-166.
J.E. Fajardo, R. Shrestha, N. Gil, A. Belsom, S.N. Crivelli, C. Czaplewski, ... A. Fiser. “Assessment of chemical-crosslink-assisted protein structure modeling in CASP13.” Proteins: Structure, Function and Bioinformatics. September 2019; Vol 87(12):1283-97. https://doi.org/10.1002/prot.25816.
M.F. Lensink, G. Brysbaert, N. Nadzirin, et al. (2019). “Blind prediction of homo- and hetero-protein complexes: The CASP13-CAPRI experiment.” Proteins. 2019; 87: 1200– 1221. https://doi.org/10.1002/prot.25838.
D.L. Brown, S.N. Crivelli, M.A. Leung (2019). “Sustainable Research Pathways: Collaborations Across Communities to Diversify the National Laboratory Workforce,” The Collaborative Network for Engineering and Computing Diversity (CoNECD), Washington, D.C., 2019, American Society for Engineering Education, Paper ID #24706.
R. Zamora-Resendiz and S. Crivelli (2019). “Structural Learning of Proteins Using Graph Convolutional Neural Networks.” https://www.biorxiv.org/content/10.1101/610444v1.

C. Keasar, L.J. McGuffin, B. Wallner, B. Adhikari, D. Bhattacharya, M. Baek, L. Bortot, R. Cao, G. Chopra, B.K. Dhanasekaran, I. Dimas, R. Faccioli, E. Faraggi, Sambit Ghosh, Soma Ghosh, L. Golon, Y. He, L. Heo, J. Hou, M. Khan, F. Khatib, G.A. Khoury, C.A. Kieslich, D.E. Kim, P. Krupa, G.R. Lee, H. Li, J. Li, A. Lipska, A. Liwo, A.H.A Maghrabi, M. Mirdita, S. Mirzaei, M.A. Mozolewska, M. Onel, S. Ovchinnikov, A. Shah, U. Shah, T. Sidi, A.K. Sieradzan, J. Smadbeck, P. Tamamis, N. Trieber, T. Wirecki, Y. Yin, Y. Zhang, J. Bacardit, M. Baranowski, N. Chapman, S. Cooper, A. Defelicibus, J. Flatten, R. Ganzynkowicz, A. Giełdoń, B. Koepnick, Z. Popović, M. Ślusarz, R. Ślusarz, B. Zaborowski, D. Baker, J. Cheng, C. Czaplewski, A. Delbem, C.A. Floudas, A. Kloczkowski, S. Ołdziej, M. Levitt, C. Seok, J. Söeding, S. Vishveshwara, D. Xu, Foldit Players, and S.N. Crivelli (2018). “An Analysis and Evaluation of the WeFold Collaborative for Protein Structure Prediction and its pipelines in CASP11 and CASP12.” Scientific Reports volume 8, Article 9939.
D. Rosa de Jesus, J. Cuevas. W. Rivera, and S. Crivelli (2018). “Capsule Networks for Protein Structure Classification and Prediction.” https://arxiv.org/pdf/1808.07475.pdf.

T. Johnston, B. Zhang, A. Liwo, S. Crivelli, and M. Taufer (2017). “In situ data analytics and indexing of protein trajectories.” Journal of Computational Chemistry. 2017, DOI: 10.1002/jcc.24729.
T. Corcoran, R. Zamora-Resendiz, X. Liu, and S. Crivelli (2017). “A Spatial Mapping Algorithm with Applications in Deep Learning-Based Structure Classification.” https://arxiv.org/pdf/1802.02532.pdf.

S. Mirzaei, T. Sidi, C. Keasar, and S.Crivelli (2016). “Purely Structural Protein Scoring Functions Using Support Vector Machine and Ensemble Learning.” IEEE/ACM Transactions on Computational Biology and Bioinformatics, Volume: PP Issue: 99. DOI: 10.1109/TCBB.2016.2602269.

S. Crivelli, R. Dooley, R. Holmes, S. Mock, and The WeFold Community (2015). “Creating a Gateway that Enables Large-Scale Science Coopetition.” Concurrency and Computation: Practice and Experience, 2015; 27(2): 446–457, doi: 10.1002/cpe.3270.

G. Khoury, A. Liwo, F. Khatib, H. Zhou, G. Chopra, J. Bacardit, L. Bortot, A.C. Delbum, X. Deng, R. Faccioli, Y. He, P. Krupa, J. Li, M. Mozolewska, D. Baker, J. Cheng, C. Floudas, C. Keasar, M. Levitt, Z. Popović, H. Scheraga, J. Skolnick, S. Crivelli & Foldit Players (2014). “WeFold: A Coopetition for Protein Structure Prediction.” Proteins: Structure, Function, and Bioinformatics; 82(9): 1850-1868, doi: 10.1002/prot.24538.