skip to Main Content


Bioinformatics/Biostatistics Methodology Research

The Department of Quantitative Health Sciences (DQHS) is a leading academic department in the John A. Burns School of Medicine for the development and application of quantitative methodology across the biomedical sciences. We also have collaborative partnerships with various research groups in Hawaii outside of the medical school.

Our skilled DQHS members are dedicated to conducting collaborative and methodological research in a wide range of areas, including study design, survey methodology, clinical trials/studies, epidemiological research, community-based research, large-scale “omics” data analysis and other basic science research, longitudinal data analysis, Bayesian methodologies, survival analysis, structural equation modeling, spatial analysis, diagnostics, non-parametric and semi-parametric methods, bioinformatics data analysis, and biomedical informatics.


Hawai‘i Single-Race Categorization Tool

The Hawai‘i Single-Race Categorization Tool is a user-friendly research tool to obtain the age and gender distributions of single-race estimates for common racial groups in Hawai‘i. It presents results in tabular and graphic formats, stratified by age and gender, and allows the categorization of partial Hawaiians as Hawaiians in the population estimation.

Hawai‘i Single-Race Categorization Tool Website


Selected Publications

  • Kulasekera KB, Siriwardhana C. Quantiles based personalized treatment selection for multivariate outcomes and multiple treatments. Statistics in Medicine. 2022 Jul 10;41(15):2695-2710. DOI: 10.1002/sim.9377. PMID: 35699385; PMCID: PMC9232994.
  • Foox J, Nordlund J, Lalancette C, Gong T, Lacey M, Lent S, Langhorst BW, Ponnaluri VKC, Williams L, Padmanabhan KR, Cavalcante R, Lundmark A, Butler D, Mozsary C, Gurvitch J, Greally JM, Suzuki M, Menor M, Nasu M, Alonso A, Sheridan C, Scherer A, Bruinsma S, Golda G, Muszynska A, Łabaj PP, Campbell MA, Wos F, Raine A, Liljedahl U, Axelsson T, Wang C, Chen Z, Yang Z, Li J, Yang X, Wang H, Melnick A, Guo S, Blume A, Franke V, Ibanez de Caceres I, Rodriguez-Antolin C, Rosas R, Davis JW, Ishii J, Megherbi DB, Xiao W, Liao W, Xu J, Hong H, Ning B, Tong W, Akalin A, Wang Y, Deng Y, Mason CE. The SEQC2 epigenomics quality control (EpiQC) study. Genome Biol. 2021 Dec 6;22(1):332. DOI: 10.1186/s13059-021-02529-2. Erratum in: Genome Biol. 2021 Dec 23;22(1):350. Erratum in: Genome Biol. 2022 Mar 8;23(1):76. PMID: 34872606; PMCID: PMC8650396.
  • Deng Y, Zhu Y, Wang H, Khadka VS, Hu L, Ai J, Dou Y, Li Y, Dai S, Mason CE, Wang Y, Jia W, Zhang J, Huang G, Jiang B. Ratio-Based Method To Identify True Biomarkers by Normalizing Circulating ncRNA Sequencing and Quantitative PCR Data. Analytical Chem. 2019 May 21;91(10):6746-6753. DOI: 10.1021/acs.analchem.9b00821. Epub 2019 Apr 30. PMID: 31002238; PMCID: PMC6884007.
  • Davis J, Lim E, Taira DA, Chen JJ. Relation of the Networks Formed by Diabetic Patients Sharing Physicians With Emergency Department Visits and Hospitalizations. Med Care. 2020 Sep;58(9):800-804. DOI: 10.1097/MLR.0000000000001378. PMID: 32826745.
  • Davis J, Lim E, Taira DA, Chen JJ. Healthcare network analysis of patients with diabetes and their physicians. Am J Manag Care. 2019 Jul 1;25(7):e192-e197. PMID: 31318509; PMCID: PMC6999614.
  • Menor M, Zhu Y, Wang Y, Zhang J, Jiang B, Deng Y. Development of somatic mutation signatures for risk stratification and prognosis in lung and colorectal adenocarcinomas. BMC Med Genomics. 2019 Jan 31;12(Suppl 1):24. DOI: 10.1186/s12920-018-0454-7. PMID: 30704450; PMCID: PMC6357362.
  • Ahn H, Chen JJ. Proportional weighting algorithm for single-race population estimation using multiracial Census data. Population Review, 2018;57(1):66-71. DOI:10.1353/prv.2018.0003.
  • Khadka VS, Wang L, Lim E, Chen JJ. Comparison of False Positive in Tools for Differential Gene Expression Calling in RNA-Seq Analysis. International Journal of Computational Bioinformatics and In Silico Modeling. 2016 September; 5(5):876-885.

Back To Top