FUNDING

Dr. So Young Ryu is a recipient of NSF CAREER, NIH/NIGMS R15, NIH/NIGMS NV INBRE DRP Award, Microsoft Azure Award, and NIH T32 fellowship.  

PATENTS

• Ryu, S.Y.* (2023). Computer-Implemented Methods and Systems for Identifying a Species from Mass Spectra. United State Patent, No.11798656. (100% inventorship for Ryu, S.Y.) 

PUBLICATIONS

*Corresponding Author; #Ryu Lab Members/Students

• Henke, C., Goodwin, G., and Ryu, S.Y.*, 2025, Lesson Plan: Mass Spectrometry and Proteomics. OER Commons, https://oercommons.org/courseware/lesson/132271.

• Rosenquist, N.*, Richards, M, ..., Ryu, S.Y., et al., 2024, Maternal obesity and childhood asthma risk: Exploring mediating pathways. Pediatric and Perinatal Epidemiology. doi: 10.1111/ppe.13023.

• Rosenquist, N.A.*, Richards, M., Ferber, J.R., Li, D., Ryu, S.Y., Burkin, H, Strickland, M.J., and Darrow., L.A., 2023. Prepregnancy Body Mass Index and Risk of Childhood Asthma. Allergy. doi: 10/1111/all.15598. 

• Goodwin, G.#* and Ryu, S.Y., 2023. Understanding the Odds: Statistics in Public Health. Frontiers for Young Minds. doi: 10.3389/frym.2022.926624.

• Bertauche, K.#* and Ryu, S.Y., 2023. Application of Machine Learning in Clear Cell Renal Cell Carcinoma Prediction. Nevada State Undergraduate Research Journal, Vol 8, No. 1, pp. 7-15. 

• Bertauche, K.#*, Alexander Choi#, and Ryu, S.Y., 2022. Predicting Retention Times of Post-translationally Modified Peptides Using Machine Learning Techniques. Proceedings of KDD-UC. ACM, New York, NY, USA. 

• Ryu, S.Y.*, 2022. Likelihood-based Bacterial Identification Approach for Bimicrobial Mass Spectrometry Data. Annals of Applied Statistics, Vol. 16, No. 1, pp. 612-624. doi: 0.1214/21-AOAS1520.

• Park, S.Y.*, Ryu, S.Y., Constantino, N., Yun, G.W., Jennings, E. and Fred, D., 2022. Marijuana knowledge, confidence in knowledge, and information efficacy as the protective and risk factors of marijuana use among college students. Journal of American College Health, pp.1-8. doi: 10.1080/07448481.2020.1751171. 

• Park, S. Y.*, Yun, G. W., Constantino, N., Ryu, S.Y., 2022. Gender differences in the risk and protective factors of marijuana use among college students. Journal of Health Psychology. doi: 10.1177/13591053211002248.

• Bertauche, K., Choi, A., Ryu, S. Y., 2022. Predicting Retention Times of Post-translationally Modified Peptides Using Machine Learning Techniques. KDD-UC, August 14-18, 2022, Washington DC, AMC, New York, NY, USA.

• Ryu, S.Y.*, Yun, M.P.#, Kim, S.#, 2021. Integrating Multiple Quantitative Proteomics Analyses using MetaMSD. In: Statistical Analysis of Proteomic Data. Springer. doi: 10.1007/978-1-0716-1967-4.  

• Brenner, R.#, Bertauche, K.#, Choi, A.#, and Ryu, S.Y.*, 2021. VA-PRT: A Visualization Tool for Analyzing Post-translational Modification Retention Times. Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine. doi: 10.1109/BIBM52615.2021.9669150. 

• Park, S.Y.*, Yun, G.W., Friedman, S., Hill, K., Ryu, S.Y, Schwenk, T., Coppes, M.J., 2020. US Direct-to-Consumer Medical Advertisements Fail to Provide Adequate Information on Quality and Cost of Care. Journal of Medical Ethics.

• Ryu, S.Y.*, Wendt, G.A.#, Ernst, R.K., Goodlett, D.R., 2020. MGMS2: Membrane Glycolipid Mass Spectrum Simulator for polymicrobial samples. Rapid Communication in Mass Spectrometry. doi: 10.1002/rcm.8824.

• Rosenquist, N.A.*, Metcalf, W.J., Ryu, S.Y., Rutledge, A., Coppes, M.J., Grzymski, J.J., Strickland, M.J. and Darrow, L.A., 2020. Acute associations between PM 2.5 and ozone concentrations and asthma exacerbations among patients with and without allergic comorbidities. Journal of Exposure Science & Environmental Epidemiology, pp.1-10. doi: 10.1038/s41370-020-0213-7.

• Park, S.Y.*, Yun, G.W., Constantino, N., Ryu, S.Y., Fred, D., Jennings, E., and Duenas, K., 2020. Health information literacy-focused marijuana intervention for college students: A pilot study of group-oriented universal program. Journal of Alcohol and Drug Education, 64(1), 33-51.

• Ryu, S.Y.*, Wendt, G.A.#, Chandler, C.E., Ernst, R.K., Goodlett, D.R., 2019. Model-based spectral library approach for bacterial identification via membrane glycolipids. Analytical Chemistry, 91(17), 11482-11487. doi: 10.1021/acs.analchem.9b03340.

• Ryu, S.Y.* and Wendt, G.A.#, 2019. MetaMSD: meta analysis for mass spectrometry data. PeerJ, 7, pp.e669. doi:10.7717/peerj.6699.

• Kamal, O.#, Li, Hanao#, Mihye Ahn*, and Ryu, S.Y.*, 2019. Predicting Pediatric Traumatic Brain Mortalities, 2018 Fall USRESP Winners. Available from https://www.causeweb.org/usproc/usresp/2018/fall/winners. doi: 10.5281/zenodo.3820475.

• Ryu, S.Y.*, 2018. Addressing varying non-ignorable missing data mechanisms using a penalized EM algorithm: application to quantitative proteomics data. Statistics and Its Interface, 11(4), pp.581-586. doi:10.4310/SII.2018.v11.n4.a3.

• Ryu, S.Y.*, 2018. Measuring Pairwise Similarity of Tandem Mass Spectra Using Pair Hidden Markov Model. IEEE ICMLC, 1, pp. 204-209. doi:10.1109/ICMLC.2018.8527013.

• Ryu, S.Y.*, Davis, R.W. and Xiao, W., 2016. Detecting common genomic mechanism between diseases using paired sparse canonical correlation analysis. IEEE ICMLC,1, pp. 117-122. doi:10.1109/ICMLC.2016.7860887.

• Ryu, S.Y., Qian, W.J., Camp, D.G., Smith, R.D., Tompkins, R.G., Davis, R.W. and Xiao, W.*, 2014. Detecting differential protein expression in large-scale population proteomics. Bioinformatics, 30(19), pp.2741-2746. doi: 10.1093/bioinformatics/btu341.

• Ryu, S.Y.*, 2014. Bioinformatics tools to identify and quantify proteins using mass spectrometry data. In Advances in protein chemistry and structural biology, 94, pp. 1-17. Academic Press. doi: 10.1016/B978-0-12-800168-4.00001-9.

• Ryu, S.Y., Payne, S.H., Schaab, C. and Xiao, W.*, 2014. Beyond the proteome: Mass Spectrometry Special Interest Group (MS-SIG) at ISMB/ECCB 2013. Bioinformatics, 30(14), p.2089-2090. doi: bioinformatics/btu116.

• Sigdel, T.K., Salomonis, N., Nicora, C.D., Ryu, S.Y., He, J., Dinh, V., Orton, D.J., Moore, R.J., Hsieh, S.C., Dai, H. and Thien-Vu, M.*, 2014. The identification of novel potential injury mechanisms and candidate biomarkers in renal allograft rejection by quantitative proteomics. Molecular & Cellular Proteomics, 13(2), pp.621-631. doi: 10.1074/mcp.M113.030577.

• Ryu, S.Y., Goodlett, D.R., Noble, W.S. and Minin, V.N.*, 2012. A statistical approach to peptide identification from clustered tandem mass spectrometry data. 2012 IEEE BIBM, 1, pp. 648-653. doi: 10.1109/BIBMW.2012.6470214.

• Chakrabarti, L.*, Zahra, R., Jackson, S.M., Kazemi-Esfarjani, P., Sopher, B.L., Mason, A.G., Toneff, T., Ryu, S.Y., Shaffer, S., Kansy, J.W. and Eng, J., 2010. Mitochondrial dysfunction in NnaD mutant flies and Purkinje cell degeneration mice reveals a role for Nna proteins in neuronal bioenergetics. Neuron, 66(6), pp.835-847. doi: 10.1016/j.neuron.2010.05.024.

• Goo, Y.A.*, Liu, A.Y., Ryu, S.Y., Shaffer, S.A., Malmström, L., Page, L., Nguyen, L.T., Doneanu, C.E. and Goodlett, D.R., 2009. Identification of secreted glycoproteins of human prostate and bladder stromal cells by comparative quantitative proteomics. Prostate, 69(1), pp.49-61. doi: 10.1002/pros.20853.

• Ryu, S.Y., Gallis, B., Goo, Y.A., Shaffer, S.A., Radulovic, D. and Goodlett, D.R.*, 2008. Comparison of a label-free quantitative proteomic method based on peptide ion current area to the isotope coded affinity tag method. Cancer Informatics, 6, pp.CIN-S385. doi: 10.4137/CIN.S385.

• Chen, J.*, Ryu, S.Y., Gharib, S.A., Goodlett, D.R. and Schnapp, L.M., 2008. Exploration of the normal human bronchoalveolar lavage fluid proteome. Proteomics - Clinical Applications, 2(4), pp.585-595.  doi: 10.1002/prca.200780006.

• Guina, T.*, Radulovic, D., Bahrami, A.J., Bolton, D.L., Rohmer, L., Jones-Isaac, K.A., Chen, J., Gallagher, L.A., Gallis, B., Ryu, S.Y. and Taylor, G.K. et al., 2007. MglA regulates Francisella tularensis subsp. novicida (Francisella novicida) response to starvation and oxidative stress. Journal of bacteriology, 189(18), pp.6580-6586. doi: 10.1128/JB.00809-07.

• Radulovic, D., Jelveh, S., Ryu, S.Y., Hamilton, T.G., Foss, E., Mao, Y. and Emili, A.*, 2004. Informatics platform for global proteomic profiling and biomarker discovery using liquid chromatography-tandem mass spectrometry. Molecular & cellular proteomics, 3(10), pp.984-997. doi: 10.1074/mcp.M400061-MCP200.

• Qian, L.*, and Ryu, S.Y., 2006. Estimating tree resin dose effect on termites. Environmetrics, 17(2), pp.183-197. doi: 10.1002/env.761.