Interests

  • Machine learning and predictive modeling
  • High-dimensional “Big Data”
  • Variable selection
  • Multi-omics cancer data integration

Publications

  1. Ni, K., Rogowitz, E., Farahmand, A. K., Kaizer, L. K., Arbet, J., Cunningham, C. R., … & Saxon, D. R. (2024). Weight Loss Outcomes in a Veterans Affairs Pharmacotherapy-based Weight Management Clinic. Journal of the Endocrine Society, 8(5), bvae042. https://doi.org/10.1210/jendso/bvae042
  2. Lippitt, W., Carlson, N. E., Arbet, J., Fingerlin, T. E., Maier, L. A., & Kechris, K. (2024). Limitations of clustering with PCA and correlated noise. Journal of Statistical Computation and Simulation, 1-29. https://doi.org/10.1080/00949655.2024.2329976
  3. Greca, A. L., Grau, L., Arbet, J., Liao, L. M., Sosa, J. A., Haugen, B. R., & Kitahara, C. M. (2023). Anthropometric, dietary, and lifestyle factors and risk of advanced thyroid cancer: The NIH‐AARP diet and health cohort study. Clinical Endocrinology, 99(6), 586-597. https://doi.org/10.1111/cen.14970
  4. Chan, T. W., Dodson, J. P., Arbet, J., Boutros, P. C., & Xiao, X. (2023). Single-cell analysis in lung adenocarcinoma implicates RNA editing in cancer innate immunity and patient prognosis. Cancer research, 83(3), 374-385. https://doi.org/10.1158/0008-5472.CAN-22-1062
  5. Gamallat Y, Choudhry M, Li Q, Rokne JG, Alhajj R, Abdelsalam R, Ghosh S, Arbet J, Boutros PC, Bismar TA. (2023) Serrate RNA Effector Molecule (SRRT) Is Associated with Prostate Cancer Progression and Is a Predictor of Poor Prognosis in Lethal Prostate Cancer. Cancers, 15(10):2867. https://doi.org/10.3390/cancers15102867
  6. Grau, L., Arbet, J., Ostendorf, D. M., Blankenship, J. M., Panter, S. L., Catenacci, V. A., … & Creasy, S. A. (2022). Creating an algorithm to identify indices of sleep quantity and quality from a wearable armband in adults. Sleep Science, 15(03), 279-287. https://doi.org/10.5935/1984-0063.20220052
  7. Creasy, S. A., Ostendorf, D. M., Blankenship, J. M., Grau, L., Arbet, J., Bessesen, D. H., … & Catenacci, V. A. (2022). Effect of sleep on weight loss and adherence to diet and physical activity recommendations during an 18-month behavioral weight loss intervention. International Journal of Obesity, 46(8), 1510-1517. https://doi.org/10.1038/s41366-022-01141-z
  8. Lin, N. W., Arbet, J., Mroz, M. M., Liao, S. Y., Restrepo, C. I., Mayer, A. S., … & Maier, L. A. (2022). Clinical phenotyping in sarcoidosis using cluster analysis. Respiratory research, 23(1), 88. https://doi.org/10.1186/s12931-022-01993-z
  9. Wood, C., Arbet, J., Amura, C. R., Nodine, P., Collins, M. R., Orlando, B. S., … & Anderson, J. (2022). Multicenter Study Evaluating Nitrous Oxide Use for Labor Analgesia at High-and Low-Altitude Institutions. Anesthesia & Analgesia, 134(2), 294-302. https://doi.org/10.1213/ane.0000000000005712
  10. Okamoto, Y., Devoe, S., Seto, N., Minarchick, V., Wilson, T., Rothfuss, H.M., Mohning, M.P., Arbet, J., Kroehl, M., Visser, A. and August, J., (2022). Association of sputum neutrophil extracellular trap subsets with IgA anti–citrullinated protein antibodies in subjects at risk for rheumatoid arthritis. Arthritis & Rheumatology, 74(1), pp.38-48. https://doi.org/10.1002/art.41948
  11. Carpenter, C. M., Frank, D. N., Williamson, K., Arbet, J., Wagner, B. D., Kechris, K., & Kroehl, M. E. (2021), “tidyMicro: a pipeline for microbiome data analysis and visualization using the tidyverse in R,” BMC Bioinformatics, 22(1), 1-13. https://doi.org/10.1186/s12859-021-03967-2
  12. Ostendorf, D. M., Blankenship, J. M., Grau, L., Arbet, J., Mitchell, N. S., Creasy, S. A., … & Catenacci, V. A. (2021). Predictors of long‐term weight loss trajectories during a behavioral weight loss intervention: an exploratory analysis. Obesity Science & Practice, 7(5), 569-582. https://doi.org/10.1002/osp4.530
  13. Nodine, P. M., Arbet, J., Jenkins, P. A., Rosenthal, L., Carrington, S., Purcell, S. K., … & Hoon, S. (2021), “Graduate nursing student stressors during the COVID-19 pandemic,” Journal of Professional Nursing, 37(4), 721-728. https://doi.org/10.1016/j.profnurs.2021.04.008
  14. Rosenthal, L., Lee, S., Jenkins, P., Arbet, J., Carrington, S., Hoon, S., … & Nodine, P. (2021), “A Survey of Mental Health in Graduate Nursing Students during the COVID-19 Pandemic,” Nurse Educator. 46.4: 215-220. https://doi.org/10.1097/nne.0000000000001013
  15. Arbet, J., Zhuang, Y., Litkowski, E., Saba, L., & Kechris, K. (2021), “Comparing Statistical Tests for Differential Network Analysis of Gene Modules,” Frontiers in Genetics, 12, 748. https://doi.org/10.3389/fgene.2021.630215
  16. Ramakrishnan, V. R., Arbet, J., Mace, J. C., Suresh, K., Shintani Smith, S., Soler, Z. M., & Smith, T. L. (2021). Predicting olfactory loss in chronic rhinosinusitis using machine learning. Chemical Senses, 46, bjab042. https://doi.org/10.1093/chemse/bjab042
  17. Arbet, J., Brokamp, C., Meinzen-Derr, J., Trinkley, K. E., & Spratt, H. M. (2021), “Lessons and tips for designing a machine learning study using EHR data,” Journal of Clinical and Translational Science, 5(1). *: Authors contributed equally to this work as first authors. https://doi.org/10.1017/cts.2020.513
  18. Thomas, E.A., Zaman, A., Cornier, M.A., Catenacci, V.A., Tussey, E.J., Grau, L., Arbet, J., Broussard, J.L. and Rynders, C.A. (2021), “Later Meal and Sleep Timing Predicts Higher Percent Body Fat,” Nutrients, 13(1), p.73. https://doi.org/10.3390/nu13010073
  19. Reed, S. M., Arbet, J., & Staubli, L. (2021), “Clinical Nurse Specialists in the United States Registered With a National Provider Identifier,” Clinical Nurse Specialist, 35(3), 119-128. https://doi.org/10.1097/nur.0000000000000592
  20. Schmanski, A., Roberts, E., Coors, M., Wicks, S. J., Arbet, J., Weber, R., … & Taylor, M. R. (2021), “Research participant understanding and engagement in an institutional, self‐consent biobank model,” Journal of Genetic Counseling, 30(1), 257-267. https://doi.org/10.1002/jgc4.1316
  21. Arbet, J., McGue, M., & Basu, S. (2020), “A robust and unified framework for estimating heritability in twin studies using generalized estimating equations,” Statistics in Medicine, 39(27), 3897-3913. https://doi.org/10.1002/sim.8564
  22. Coleman-Minahan, K., Sheeder, J., Arbet, J., & McLemore, M. R. (2020), “Interest in Medication and Aspiration Abortion Training among Colorado Nurse Practitioners, Nurse Midwives, and Physician Assistants,” Women’s Health Issues, 30(3), 167-175. https://doi.org/10.1016/j.whi.2020.02.001
  23. Gance-Cleveland, B., Linton, A., Arbet, J., Stiller, D., & Sylvain, G. (2020), “Predictors of Overweight and Obesity in Childhood Cancer Survivors,” Journal of Pediatric Oncology Nursing, 37(3), 154-162. https://doi.org/10.1177%2F1043454219897102
  24. James-Allan, L. B., Arbet, J., Teal, S. B., Powell, T. L., & Jansson, T. (2019), “Insulin stimulates GLUT4 trafficking to the syncytiotrophoblast basal plasma membrane in the human placenta,” The Journal of Clinical Endocrinology & Metabolism, 104(9), 4225-4238. https://doi.org/10.1210/jc.2018-02778
  25. Arbet, J., McGue, M., Chatterjee, S., & Basu, S. (2017), “Resampling-based tests for Lasso in genome-wide association studies,” BMC Genetics, 18(1), 1-15. https://doi.org/10.1186/s12863-017-0533-3
  26. Grinde, K. E., Arbet, J., Green, A., O’Connell, M., Valcarcel, A., Westra, J., & Tintle, N. (2017), “Illustrating, quantifying, and correcting for bias in post-hoc analysis of gene-based rare variant tests of association,” Frontiers in Genetics, 8, 117. https://doi.org/10.3389/fgene.2017.00117
  27. Greco, B., Hainline, A., Arbet, J., Grinde, K., Benitez, A., & Tintle, N. (2016), “A general approach for combining diverse rare variant association tests provides improved robustness across a wider range of genetic architectures,” European Journal of Human Genetics, 24(5), 767-773. https://doi.org/10.1038/ejhg.2015.194