Biostatistics is the study of the application of statistical inference and methods to health-related fields such as public health, medicine, and biology. As one of the core disciplines of public health, it is concerned with the quantitative aspects of the design, conduct, analysis, and interpretation of health science research.
Biostatistical methods are used in a wide range of public health activities, including assessing causal hypotheses of disease and injury, evaluating the effectiveness of intervention programs/policies/trials, and monitoring and detecting population health trends.
Our faculty are engaged in the development and application of biostatistical methods and their teaching for a wide range of research in public health. The development of the methodologies we pursue is always done through collaboration with researchers in other health-related fields, such as public health and medicine.
Our research is usually funded by government agencies such as the Ministry of Education, Culture, Sports, Science and Technology and the Ministry of Health, Labor and Welfare. In addition to developing methodologies, each biostatistics faculty member is very active in interdisciplinary collaborations with regional, national, and international researchers and governments.
Current projects
Bioinformatics for OMICS data, including comprehensive genomic data from next-generation sequencers, gene expression data from microarrays, and protein expression data from mass spectrometers, for the realization of personalized medicine.
Development of systems for predicting therapeutic effects and side effects based on statistical analysis
Statistical analysis of OMICS data to search for seeds of drug discovery
Statistical analysis of OMICS data for drug discovery ・ Research on statistical data analysis methodologies for diagnosis support for cancer patients, such as cancer subtype determination
Research on statistical data analysis methodologies to support diagnosis of cancer patients, such as determination of cancer subtypes ・Development of longitudinal data analysis models using large-scale cohort data to elucidate the risk of heart failure
Development of a longitudinal data analysis model using large-scale cohort data to elucidate the risk of heart failure
Discovery of novel pathogenic molecules for thoracic aortic aneurysm and development of therapeutic strategies (early diagnosis and drug discovery)
Support for research planning and appropriate analysis of clinical trials for pharmaceuticals and health foods
Research on drug development and evaluation of the efficacy and safety of drugs, etc., including application of simulation in drug development and pharmacoepidemiological research
