Program Disclaimer:
Within the next academic year, the Division of Biostatistics and Bioinformatics will merge into the newly named Department of Biostatistics, Health Informatics, and Data Sciences (BHIDS) within the College of
Medicine. This will create a better platform for faculty and students in the Data Sciences to further their research and research opportunities.
The Master of Science and Doctoral programs in Environmental Health-Biostatistics will also merge into BHIDS and undergo a name change to represent the program's new home better. Future admitted students will be eligible to obtain their degree with
the new name if they choose.
Biostatistics and Bioinformatics
Housed in UC’s department of Environmental and Public Health Sciences with collaborations throughout the College of Medicine and Cincinnati Children’s Hospital Medical Center, the Division of Biostatistics and Bioinformatics offers exciting
training and research opportunities in biomedical data sciences. Training programs in the division combine rigorous statistical and computational education rooted in the probability theory and computer science with the exposure to a broad range of
biomedical research applications.
Biostatistics is a data science field concerned with application of statistical reasoning in the biomedical and public health research. Biostatisticians develop statistical methodologies that are tailored to address specific biomedical data analysis problems.
Biostatisticians are also members of interdisciplinary biomedical research teams whose role is to ensure optimal use of data to answer specific biomedical research questions.
Bioinformatics is an interdisciplinary field that develops methods and computational tools for understanding high-dimensional biomedical data. Bioinformatics combines computer science, statistics, mathematics, and engineering to manage, process and analyze
biomedical data. There and many overlaps between Biostatistics and Bioinformatics in terms of methodologies utilized and domains of application in biomedical research. However, Bioinformatics tends to be more focused on the analysis and interpretation
of high dimensional datasets such as genomics, proteomics and metabolomics. Furthermore, Bioinformatics research objectives often involve development of software tools that facilitates management and analysis of large and complex datasets.
Both Biostatistics and Bioinformatics are integral parts of the new emerging field of Biomedical Data Sciences. Data Sciences in general is a field dedicated to extraction knowledge from data. In the context of the biomedical and public health research,
data sciences integrate traditional statistical reasoning with the technological and computational solutions needed to organize, integrate and analyze relevant data. The biomedical and public health research is increasingly becoming data-intensive
and data-driven. The challenges and opportunities offered by accessing, managing, analyzing, and integrating datasets of diverse data types (exposure, health, behavioral, genomics, genetics, etc) is captured by the term “Big Data”. The
graduate programs and research within our division reflect rapidly increasing role that the data sciences play in contemporary biomedical and public health research.
Current methodological research undertaken by division faculty includes statistical methods for multiple hypothesis testing, statistical genetics, supervised and unsupervised Bayesian and machine learning methods for genomics data analysis, methods for
next generation sequencing data analysis, statistical geospatial modeling, integrative statistical models for Big Data, computational drug screening, and protein structure modeling.
A few examples of interdisciplinary biomedical research projects that involve division faculty are study of predictive transcriptional signature for juvenile idiopathic arthritis, genomic determinants of kidney cancer, cancer treatment clinical trials,
and numerous biomedical projects investigating gene-environment interactions.
A Sample of Recent Publications by the Division of Biostatistics and Bioinformatics
Dr. Roman Jandarov
- Merianos AL, Jandarov RA, Mahabee-Gittens EM. Association of secondhand smoke exposure with asthma symptoms, medication use, and healthcare utilization among asthmatic adolescents (2019). Journal of Asthma 56(4):369-379. doi: 10.1080/02770903.2018.1463379. PubMed PMID: 29641269; PubMed Central PMCID: PMC6181790.
- Merianos AL, Jandarov RA, Klein JD, Mahabee-Gittens EM. Characteristics of Daily E-Cigarette Use and Acquisition Means Among a National Sample of Adolescents (2019). Am J Health Promotion 33(8):1115-1122. doi: 10.1177/0890117119854051. PubMed PMID: 31159556; PubMed Central PMCID: PMC6824948.
Dr. Mario Medvedovic
- Choobdar S, Ahsen ME, Crawford J, Tomasoni M, Fang T, Lamparter D, Lin J, Hescott B, Hu X, Mercer J, Natoli T, Narayan R; DREAM Module Identification Challenge Consortium (Medvedovic M), Subramanian A, Zhang JD, Stolovitzky G, Kutalik Z, Lage K, Slonim DK, Saez-Rodriguez J, Cowen LJ, Bergmann S, Marbach D. (2019). Assessment of network module identification across complex diseases. Nature Methods 16(9):843-852. doi: 10.1038/s41592-019-0509-5. Epub 2019 Aug 30. PMID: 31471613; PMCID: PMC6719725.
- Reigle J, Secic D, Biesiada J, Wetzel C, Shamsaei B, Chu J, Zang Y, Zhang X, Talbot NJ, Bischoff ME, Zhang Y, Thakar CV, Gaitonde K, Sidana A, Bui H, Cunningham JT, Zhang Q, Schmidt LS, Linehan WM, Medvedovic M, Plas DR, Landero Figueroa JA, Meller J, Czyzyk-Krzeska MF (2020). Tobacco smoking induces metabolic reprogramming of renal cell carcinoma. Journal of Clinical Investigation, doi: 10.1172/JCI140522. Online ahead of print. PMID: 32970633
- Ren Y, Sivaganesan S, Clark NA, Zhang L, Biesiada J, Niu W, Plas DR, Medvedovic M. (2020). Predicting mechanism of action of cellular perturbations with pathway activity signatures. Bioinformatics, doi: 10.1093/bioinformatics/btaa590. Epub ahead of print. PMID: 32653926.
- Shamsaei B, Chojnacki S, Pilarczyk M, Najafabadi M, Niu W, Chen C, Ross K, Matlock A, Muhlich J, Chutipongtanate S, Zheng J, Turner J, Vidović D, Jaffe J, MacCoss M, Wu C, Pillai A, Ma'ayan A, Schürer S, Kouril M, Medvedovic M, Meller J. (2020). piNET: a versatile web platform for downstream analysis and visualization of proteomics data. Nucleic Acids Research 48(W1):W85-W93. doi: 10.1093/nar/gkaa436. PMID: 32469073; PMCID: PMC7319557
- Weichun Huang, Mario Medvedovic, Jingwen Zhang and Liang Niu (2019). ChIAPoP: a new tool for ChIA-PET data analysis. Nucleic Acids Research 47 (7), e37.
Dr. Jaroslaw Meller
- Reigle J, Secic D, Biesiada J, Wetzel C, Shamsaei B, Chu J, Zang Y, Zhang X, Talbot NJ, Bischoff ME, Zhang Y, Thakar CV, Gaitonde K, Sidana A, Bui H, Cunningham JT, Zhang Q, Schmidt LS, Linehan WM, Medvedovic M, Plas DR, Landero Figueroa JA, Meller J, Czyzyk-Krzeska MF (2020). Tobacco smoking induces metabolic reprogramming of renal cell carcinoma. Journal of Clinical Investigation, doi: 10.1172/JCI140522. Online ahead of print. PMID: 32970633
- Shamsaei B, Chojnacki S, Pilarczyk M, Najafabadi M, Niu W, Chen C, Ross K, Matlock A, Muhlich J, Chutipongtanate S, Zheng J, Turner J, Vidović D, Jaffe J, MacCoss M, Wu C, Pillai A, Ma'ayan A, Schürer S, Kouril M, Medvedovic M, Meller J. (2020). piNET: a versatile web platform for downstream analysis and visualization of proteomics data. Nucleic Acids Research 48(W1):W85-W93. doi: 10.1093/nar/gkaa436. PMID: 32469073; PMCID: PMC7319557
Dr. Liang Niu
- Weichun Huang, Mario Medvedovic, Jingwen Zhang and Liang Niu (2019). ChIAPoP: a new tool for ChIA-PET data analysis. Nucleic Acids Research 47 (7), e37.
- Zongli Xu, Changchun Xie, Jack Taylor and Liang Niu, ipDMR: Identification of differentially methylated regions with interval P-values, Bioinformatics, btaa732, 2020.
Dr. MB Rao
- Benjamin ML, Arnold S, Rao M, Davis K, Maier A, Virkutyte J. (2020). Ventilation and posture effects on inhalation exposures to volatile cleaning ingredients in a simulated domestic worker cleaning environment. Indoor Air, doi: 10.1111/ina.12715. Epub ahead of print. PMID: 32648981.
- Bernstein JA, Singh U, Rao MB, Berendts K, Zhang X, Mutasim D. (2020). Benralizumab for Chronic Spontaneous Urticaria. The New England Journal of Medicine 383(14):1389-1391. doi: 10.1056/NEJMc2016395. PMID: 32997916.
Dr. Changchung Xie
- Inge, T. H., Courcoulas, A. P., Jenkins, T., Michalsky, M., Brandt, M. L., Xanthakos, S. A., Dixon, J. B., Harmon, C. M., Chen, M. K., Xie, C., Evans, M. E. and Helmrath, M. A. (2019). Five year outcomes of gastric bypass in adolescents compared to adults. The New England Journal of Medicine 380(22):2136-2145. PMID: 31116917.
- Xie, C., Leung, Y. K., Chen, A., Long, D. X., Hoyo, C. and Ho, S. M. (2019). Differential methylation values in differential methylation analysis. Bioinformatics35(7):1094-1097. doi: 10.1093/bioinformatics/bty778.
- Zongli Xu, Changchun Xie, Jack Taylor and Liang Niu, ipDMR: Identification of differentially methylated regions with interval P-values, Bioinformatics, btaa732, 2020.
Annette Christianson
- Shah S, Christianson AL, Meganathan K, Leonard AC, Schauer DP, Thakar CV. (2019). Racial differences and factors associated with pregnancy in ESKD patients on dialysis in the United States. Journal of the Americal Society of Nephrology, doi: 10.1681/ASN.2019030234. Epub 2019 September 25. PMID: 31554657.
- Shah S, Meganathan K, Christianson AL, Harrison K, Leonard AC, Thakar CV. (2020). Pregnancy-related acute kidney injury in the United States: Clinical outcomes and health care utilization. American Journal of Nephrology. 2020;51(3):216-226. doi: 10.1159/000505894. Epub 2020 Feb 11. PMID: 32045905; PMCID: PMC7158232.
Karthikeyan Meganathan
- Shah S, Christianson AL, Meganathan K, Leonard AC, Schauer DP, Thakar CV. (2019). Racial differences and factors associated with pregnancy in ESKD patients on dialysis in the United States. Journal of the Americal Society of Nephrology, doi: 10.1681/ASN.2019030234. Epub 2019 September 25. PMID: 31554657.
- Shah S, Meganathan K, Christianson AL, Harrison K, Leonard AC, Thakar CV. (2020). Pregnancy-related acute kidney injury in the United States: Clinical outcomes and health care utilization. American Journal of Nephrology. 2020;51(3):216-226. doi: 10.1159/000505894. Epub 2020 Feb 11. PMID: 32045905; PMCID: PMC7158232.
Dr. Wei-Wen Hsu
Li, Yiming; Hsu, Wei-Wen (2022. ) A classification for complex imbalanced data in disease screening and early diagnosis. Statistics in medicine, , 41 (19 ) ,3679-3695More Information
Hsu, Wei-Wen; Mawella, Nadeesha R; Todem, David (2022. ) On testing for homogeneity with zero-inflated models through the lens of model misspecification.International statistical review = Revue internationale de statistique, , 90 (1 ) ,62-77More Information
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Department of Environmental & Public Health Sciences
Division of Biostatistics and Bioinformatics
Kettering Lab Building
Room 133
160 Panzeca Way
Cincinnati, OH 45267-0056
Mail Location: 0056
Phone: 513-558-5704
Email: ehgrad@uc.edu