Department of Biostatistics

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Professor and Chair Kim-Anh Do

About Dr. Do

Kim-Anh Do, Ph.D., is Professor in the Department of Biostatistics at MD Anderson, a recipient of the Faculty Scholar Award at MD Anderson in 2003. She is a Fellow of the American Statistical Association, the American Association for the Advancement of Science (AAAS) and the Royal Statistical Society and is an Elected Member of the International Statistical Institute.

She has served as a primary statistician or co-investigator on several National Institutes of Health (NIH) funded grants and clinical trials in prostate cancer, epidemiology, leukemia, upper aerodigestive cancer, breast cancer and brain cancer, including the Early Detection Research Network (EDRN) grant, the Prostate SPORE (as Director of the Biostatistics Core), the Breast SPORE, and the Brain SPORE at MD Anderson.

She has significant publications in statistical methodology, computing, biomedical, and in other applied specialist journals. Her most recent interest is in the development of clustering and analytic methods for genomic and proteomic expressions. She has developed bioinformatics software and authored books: (i) Analyzing microarray gene expression data; (ii) Bayesian Inference for Gene Expression and Proteomics; and (iii) Advances in Statistical Bioinformatics–Models and Integrative Inference for High-Throughput Data.

Her extensive contribution to statistical, medical and cancer research has resulted in more than 200 published articles to date. Additional information regarding Dr. Do’s educational and professional activities can be found here.

Education

  • B.Sc. (Mathematics and Computer Science, First Class Honors, University of Queensland, 1983),
  • M.S. (Statistics, Stanford University, 1985),
  • Ph.D. (Statistics, Stanford University, 1990).

Selected Publications

Peer-Reviewed Articles

  1. Kim J, Do KA, Ha MJ, Peterson CB. Bayesian inference of hub nodes across multiple networks. Biometrics 75(1):172-182, 2019. e-Pub 2018. PMID: 30051914.
  2. Ha MJ, Banerjee S, Akbani R, Liang L, Mills GB, Do KA, Baladandayuthapani V. Personalized Integrated Network Modeling of the Cancer Proteome Atlas. Sci Rep 8(1):14924, 2018. e-Pub 2018. PMID: 30297783.
  3. Class CA, Ha MJ, Baladandayuthapani V, Do KA. iDINGO - Integrative Differential Network Analysis in Genomics with Shiny Application. Bioinformatics 34(7):1243-1245, 2018. e-Pub 2017. PMID: 29194470.
  4. Tayob N, Stingo F, Do KA, Lok ASF, Feng Z. A Bayesian Screening Approach for Hepatocellular Carcinoma using Multiple Longitudinal Biomarkers. Biometrics 74(1):249-259, 2018. e-Pub 2017. PMID: 28482112.
  5. Chekouo T, Stingo FC, Doecke JD, Do KA. A Bayesian integrative approach for multi-platform genomic data: A kidney cancer case study. Biometrics 73(2):615-624, 2017. e-Pub 2016. PMID: 27669160.
  6. Hunt KK, Karakas C, Ha MJ, Biernacka A, Yi M, Sahin AA, Adjapong O, Hortobagyi GN, Bondy M, Thompson P, Cheung KL, Ellis IO, Bacus S, Symmans WF, Do KA, Keyomarsi K. Cytoplasmic Cyclin E Predicts Recurrence in Patients with Breast Cancer. Clin Cancer Res 23(12):2991-3002, 2017. e-Pub 2016. PMID: 27881578.
  7. Jonasch E, Hasanov E, Corn PG, Moss T, Shaw KR, Stovall S, Marcott V, Gan B, Bird S, Wang X, Do KA, Altamirano PF, Zurita AJ, Doyle LA, Lara PN, Tannir NM. A randomized phase 2 study of MK-2206 versus everolimus in refractory renal cell carcinoma. Ann Oncol 28(4):804-808, 2017. PMID: 28049139.
  8. Çeliktas M, Tanaka I, Tripathi SC, Fahrmann JF, Aguilar-Bonavides C, Villalobos P, Delgado O, Dhillon D, Dennison JB, Ostrin EJ, Wang H, Behrens C, Do KA, Gazdar AF, Hanash SM, Taguchi A. Role of CPS1 in Cell Growth, Metabolism, and Prognosis in LKB1-Inactivated Lung Adenocarcinoma. J Natl Cancer Inst 109(3):1-9, 2017. PMID: 28376202.
  9. Yang Q, Chen LS, Ha MJ, Do KA, Neelapu SS, Gandhi V. Idelalisib Impacts Cell Growth through Inhibiting Translation-Regulatory Mechanisms in Mantle Cell Lymphoma. Clin Cancer Res 23(1):181-192, 2017. e-Pub 2016. PMID: 27342398.
  10. An X, Hu J, Do KA. SIFORM: shared informative factor models for integration of multi-platform bioinformatic data. Bioinformatics 32(21):3279-3290, 2016. e-Pub 2016. PMID: 27381342.
  11. Tayob N, Do KA, Feng Z. Unbiased estimation of biomarker panel performance when combining training and testing data in a group sequential design. Biometrics 72(3):888-96, 2016. e-Pub 2016. PMID: 26845527.
  12. Jiang Y, Chen HC, Su X, Thompson PA, Liu X, Do KA, Wierda W, Keating MJ, Plunkett W. ATM function and its relationship with ATM gene mutations in chronic lymphocytic leukemia with the recurrent deletion (11q22.3-23.2). Blood Cancer J 6(6, e465):e465, 2016. e-Pub 2016. PMID: 27588518.
  13. Kebriaei P, Singh H, Huls MH, Figliola MJ, Bassett R, Olivares S, Jena B, Dawson MJ, Kumaresan PR, Su S, Maiti S, Dai J, Moriarity B, Forget MA, Senyukov V, Orozco A, Liu T, McCarty J, Jackson RN, Moyes JS, Rondon G, Qazilbash M, Ciurea S, Alousi A, Nieto Y, Rezvani K, Marin D, Popat U, Hosing C, Shpall EJ, Kantarjian H, Keating M, Wierda W, Do KA, Largaespada DA, Lee DA, Hackett PB, Champlin RE, Cooper LJ. Phase I trials using Sleeping Beauty to generate CD19-specific CAR T cells. J Clin Invest 126(9):3363-76, 2016. e-Pub 2016. PMID: 27482888.
  14. Caruso HG, Torikai H, Zhang L, Maiti S, Dai J, Do KA, Singh H, Huls H, Lee DA, Champlin RE, Heimberger AB, Cooper LJ. Redirecting T-Cell Specificity to EGFR Using mRNA to Self-limit Expression of Chimeric Antigen Receptor. J Immunother 39(5):205-17, 2016. PMID: 27163741.
  15. Kim J, Davis JW, Klein EA, Magi-Galluzzi C, Lotan Y, Ward JF, Pisters LL, Basler JW, Pettaway CA, Stephenson A, Li Ning Tapia EM, Efstathiou E, Wang X, Do KA, Lee JJ, Gorlov IP, Vornik LA, Hoque AM, Prokhorova IN, Parnes HL, Lippman SM, Thompson IM, Brown PH, Logothetis CJ, Troncoso P. Tissue Effects in a Randomized Controlled Trial of Short-term Finasteride in Early Prostate Cancer. EBioMedicine 7:85-93, 2016. e-Pub 2016. PMID: 27322462.
  16. Tayob N, Lok AS, Do KA, Feng Z. Improved Detection of Hepatocellular Carcinoma by Using a Longitudinal Alpha-Fetoprotein Screening Algorithm. Clin Gastroenterol Hepatol 14(3):469-475, 2016. e-Pub 2015. PMID: 26260109.
  17. Powell E, Shao J, Yuan Y, Chen HC, Cai S, Echeverria GV, Mistry N, Decker KF, Schlosberg C, Do KA, Edwards JR, Liang H, Piwnica-Worms D, Piwnica-Worms H. p53 deficiency linked to B cell translocation gene 2 (BTG2) loss enhances metastatic potential by promoting tumor growth in primary and metastatic sites in patient-derived xenograft (PDX) models of triple-negative breast cancer. Breast Cancer Res 18(1):13, 2016. e-Pub 2016. PMID: 26818199.
  18. Chekouo T, Stingo FC, Guindani M, Do KA. A Bayesian predictive model for imaging genetics with application to schizophrenia. Annals of Applied Statistics 10(3):1547-1571, 2016.
  19. Ha MJ, Baladandayuthapani V, Do KA. DINGO: Differential Network Analysis in Genomics. Bioinformatics 31(21):3413-3420, 2015. e-Pub 2015. PMID: 26148744.
  20. Wang Y, Hobbs BP, Hu J, Ng CS, Do KA. Predictive classification of correlated targets with application to detection of metastatic cancer using functional CT imaging. Biometrics 71(3):792-802, 2015. e-Pub 2015. PMID: 25851056.
  21. Chekouo T, Stingo FC, Doecke JD, Do KA. Incorporating microRNA regulatory network and pathways: a Bayesian graphical approach to the selection of miRNAs and genes with censored outcomes. Biometrics 71(2):428-38, 2015. e-Pub 2015. PMID: 25639276.
  22. Rembach A, Stingo FC, Peterson C, Vannucci M, Do KA, Wilson WJ, Macaulay SL, Ryan TM, Martins RN, Ames D, Masters CL, Doecke JD, AIBL Research Group. Bayesian graphical network analyses reveal complex biological interactions specific to Alzheimer’s disease. J Alzheimers Dis 44(3):917-25, 2015. PMID: 25613103.
  23. Ha MJ, Baladandayuthapani V, Do KA. Prognostic gene signature identification using causal structure learning: applications in kidney cancer. Cancer Inform 14(Suppl 1):23-35, 2015. e-Pub 2015. PMID: 25861215.
  24. Tam CS, O’Brien S, Plunkett W, Wierda W, Ferrajoli A, Wang X, Do KA, Cortes J, Khouri I, Kantarjian H, Lerner S, Keating MJ. Life After FCR: Outcomes of patients with chronic lymphocytic leukemia who progress after frontline treatment with Fludarabine, Cyclophosphamide and Rituximab. Blood 124(20):3059-64, 2014. e-Pub 2014. PMID: 25281606.
  25. Hassan B, Akcakanat A, Sangai T, Evans KW, Adkins F, Eterovic AK, Zhao H, Chen K, Chen H, Do KA, Xie SM, Holder AM, Naing A, Mills GB, Meric-Bernstam F. Catalytic mTOR inhibitors can overcome intrinsic and acquired resistance to allosteric mTOR inhibitors. Oncotarget 5(18):8544-57, 2014. e-Pub 2014. PMID: 25261369.
  26. Pande M, Bondy ML, Do KA, Sahin AA, Ying J, Mills GB, Thompson PA, Brewster AM. Association between germline single nucleotide polymorphisms in the PI3K-AKT-mTOR pathway, obesity, and breast cancer disease-free survival. Breast Cancer Res Treat 147(2):381-7, 2014. e-Pub 2014. PMID: 25108739.
  27. Zhang L, Baladandayuthapani V, Mallick BK, Manyam GC, Thompson PA, Bondy ML, Do KA. Bayesian hierarchical structured variable selection methods with application to MIP studies in breast cancer. J R Stat Soc Ser C Appl Stat 63(4):595-620, 2014. PMID: 25705056.
  28. Meric-Bernstam F, Akcakanat A, Chen H, Sahin A, Tarco E, Carkaci S, Adrada BE, Singh G, Do KA, Garces ZM, Mittendorf E, Babiera G, Bedrosian I, Hwang R, Krishnamurthy S, Symmans WF, Gonzalez-Angulo AM, Mills GB. Influence of Biospecimen Variables on Proteomic Biomarkers in Breast Cancer. Clin Cancer Res 20(14):3870-83, 2014. e-Pub 2014. PMID: 24895461.
  29. Blanco E, Sangai T, Wu S, Hsiao A, Ruiz-Esparza GU, Gonzalez-Delgado CA, Cara FE, Granados-Principal S, Evans KW, Akcakanat A, Wang Y, Do KA, Meric-Bernstam F, Ferrari M. Colocalized delivery of rapamycin and paclitaxel to tumors enhances synergistic targeting of the PI3K/Akt/mTOR pathway. Mol Ther 22(7):1310-9, 2014. e-Pub 2014. PMID: 24569835.
  30. Gonzalez-Angulo AM, Akcakanat A, Liu S, Green MC, Murray JL, Chen H, Palla SL, Koenig KB, Brewster AM, Valero V, Ibrahim NK, Moulder-Thompson S, Litton JK, Tarco E, Moore J, Flores P, Crawford D, Dryden MJ, Symmans WF, Sahin A, Giordano SH, Pusztai L, Do KA, Mills GB, Hortobagyi GN, Meric-Bernstam F. Open-label randomized clinical trial of standard neoadjuvant chemotherapy with paclitaxel followed by FEC versus the combination of paclitaxel and everolimus followed by FEC in women with triple receptor-negative breast cancer . Ann Oncol 25(6):1122-7, 2014. e-Pub 2014. PMID: 24669015.
  31. Doecke JD, Chekouo T, Stingo FC, and Do K-A. miRNA target gene identification: sourcing miRNA-target gene relationships for the analyses of TCGA Illumina miSeq and RNA-Seq Hiseq platform data. International Journal of Human Genetics 14(1):17-22, 2014.
  32. Chavez-Macgregor M, Liu S, De Melo-Gagliato D, Chen H, Do KA, Pusztai L, Fraser Symmans W, Nair L, Hortobagyi GN, Mills GB, Meric-Bernstam F, Gonzalez-Angulo AM. Differences in gene and protein expression and the effects of race/ethnicity on breast cancer subtypes. Cancer Epidemiol Biomarkers Prev 23(2):316-23, 2014. e-Pub 2013. PMID: 24296856.
  33. Gorlov IP, Yang JY, Byun J, Logothetis C, Gorlova OY, Do KA, Amos C. How to get the most from microarray data: advice from reverse genomics. BMC Genomics 15:223, 2014. e-Pub 2014. PMID: 24656147.
  34. Liu Y, Zhou R, Baumbusch LO, Tsavachidis S, Brewster AM, Do KA, Sahin A, Hortobagyi GN, Taube JH, Mani SA, Aarøe J, Wärnberg F, Børresen-Dale AL, Mills GB, Thompson PA, Bondy ML. Genomic copy number imbalances associated with bone and non-bone metastasis of early-stage breast cancer. Breast Cancer Res Treat 143(1):189-201, 2014. e-Pub 2013. PMID: 24305980.
  35. Shirazi F, Farmakiotis D, Yan Y, Albert N, Do KA, Kim-Anh D, Kontoyiannis DP. Diet modification and Metformin have a beneficial cial effect in a model of obesity and mucormycosis. PLoS One 9(9):e108635, 2014. e-Pub 2014. PMID: 25268492.
  36. León-Novelo LG, Müller P, Arap W, Sun J, Pasqualini R, Do KA. Bayesian decision theoretic multiple comparison procedures: an application to phage display data. Biom J 55(3):478-89, 2013. e-Pub 2012. PMID: 23281047.
  37. León-Novelo LG, Müller P, Arap W, Kolonin M, Sun J, Pasqualini R, Do KA. Semiparametric Bayesian Inference for Phage Display Data. Biometrics 69(1):174-83, 2013. e-Pub 2013. PMID: 23339534.
  38. Wang W, Baladandayuthapani V, Morris JS, Broom BM, Manyam G, Do KA. iBAG: integrative Bayesian analysis of high-dimensional multi-platform genomics data. Bioinformatics 29(2):149-59, 2013. e-Pub 2012. PMID: 23142963.
  39. Wang W, Baladandayuthapani V, Holmes CC, Do KA. Integrative network-based Bayesian analysis of diverse genomics data. BMC Bioinformatics 14 Suppl 13:S8, 2013. e-Pub 2013. PMID: 24267288.
  40. Bonato V, Baladandayuthapani V, Broom BM, Sulman EP, Aldape KD, Do KA. Bayesian ensemble methods for survival prediction in gene expression data. Bioinformatics 27(3):359-67, 2011. e-Pub 2010. PMID: 21148161.
  41. Zhang S, Mueller P, Do KA. A Bayesian Semiparametric Survival Model with Longitudinal Markers. Biometrics 66(2):435-43, 2010. e-Pub 2009. PMID: 19508243.
  42. Ji Y, Yin G, Tsui K-W, Kolonin MG, Sun J, Arap W, Pasqualini R, Do K-A. Bayesian mixture models for complex high dimensional count data in phage display experiments. Journal of the Royal Statistical Society: Series C (Applied Statistics) 56(2):139-52, 2007.
  43. Do K-A, McLachlan GJ, Bean R, Wen S. Gene shaving versus mixture models for the clustering of microarray gene expression data. Cancer Informatics 2:25-43, 2007. PMID: No PubMed.
  44. Kim SJ, Uehara H, Yazici S, Busby JE, Nakamura T, He J, Maya M, Logothetis C, Mathew P, Wang X, Do KA, Fan D, Fidler IJ. Targeting platelet-derived growth factor receptor on endothelial cells of multidrug-resistant prostate cancer. J Natl Cancer Inst 98(11):783-93, 2006. PMID: 16757703.
  45. Do K-A Mueller P, Tang F. A Bayesian mixture model for differential gene expression. Journal of the Royal Statistical Society, Series C-Applied Statistics 54(3):1-18, 2005. PMID: No PubMed.
  46. Do KA, Johnson MM, Lee JJ, Wu XF, Dong Q, Hong WK, Khuri FR, Spitz MR. Longitudinal study of smoking patterns in relation to the development of smoking-related secondary primary tumors in patients with upper aerodigestive tract malignancies. Cancer 101(12):2837-42, 2004. PMID: 15536619.
  47. Do K-A, Green A, Guthrie JR, Dudley EC, Burger HG, Dennerstein L. Longitudinal study of risk factors for coronary heart disease across the menopausal transition. Am J Epidemiol 151:584-93, 2000. PMID: 10733040.
  48. Do K-A, Kirk K. Discriminant analysis of event-related potential curves using smoothed principal components. Biometrics 55:174-81, 1999. PMID: 11318152.
  49. Wood ATA, Do K-A, Broom BM. Sequential linearization of empirical likelihood constraints with application to U-statistics. Journal of Computational and Graphical Statistics 5:365-85, 1996.
  50. Booth JG, Do K-A. Simple and efficient methods for constructing bootstrap confidence intervals. Computational Statistics 8:333-46, 1994.
  51. Do K-A, Hall P. Distribution estimation using concomitants of order statistics, with application to Monte Carlo stimulation for the bootstrap. Journal of the Royal Statistical Society, Series B 54:1-14, 1992.
  52. Do K-A, Hall P. On importance sampling for the bootstrap. Biometrika 78:161-167, 1991.
  53. Do K-A, McLachlan GJ. Estimation of mixing proportions: a case study. Applied Statistics 33:134-40, 1984.
  54. Brewster AM, Do KA, Thompson PA, Hahn KM, Sahin AA, Cao Y, Stewart MM, Murray JL, Hortobagyi GN, Bondy ML. Relationship between epidemiologic risk factors and breast cancer recurrence. J Clin Oncol 25(28):4438-44. e-Pub 2007. PMID: 17785707.

Book Chapters

  1. Huang X, Do K-A. Commentary on: A novel case-control design to estimate the extent of overdiagnosis of breast cancer due to organised population-based mammography screening. In: Breast Diseases: A Year Book Quarterly, 211-214, 2015.
  2. Broom BM, Do K-A, Bondy M, Thompson P, Coombes K. Methods for the analysis of copy number data in cancer research. In: Advances in Statistical Bioinformatics: Models and Integrative Inferences for High-Throughput Data. Cambridge University Press, 2013.
  3. Wang W, Baladandayuthapani V, Broom BM, Do K-A. Bayesian graphical models for integrating multi-platform genomics data. Methods for the analysis of copy number data in cancer research. In: Advances in Statistical Bioinformatics: Models and Integrative Inferences for High-Throughput Data. Cambridge University Press, 2013.
  4. Wang W, Baladandayuthapani V, Broom BM,Do K-A. Bayesian graphical models for multi-platform high-dimensional data. In: Advances in Statistical Bioinformatics: Models and Integrative Inference for High-Throughput Data. Cambridge University Press, 2013.

Books (edited and written)

  1. Do K-A, Qin Z, Vannucci M.. Advances in Statistical Bioinformatics: Models and Integrative Inferences for High-Throughput Data. Cambridge University Press, 2013.
  2. Do K-A, Müller P, Vannucci M. Bayesian Inference for Gene Expression and Proteomics. Cambridge University Press, 456, 2006.
  3. McLachlan GJ, Do K-A, Ambroise C. Analyzing Microarray Gene Expression Data. In: Wiley Series in Probability and Statistics. Wiley-Interscience: New Jersey, 352, 2004.