Statistical methods for data generated by biotechnologies

Rapid advancements in biotechnologies made possible novel studies to tackle chronic diseases such as breast cancer, or provide new insights into the role played by gut bacteria in a variety of chronic conditions. Data generated by biotechnologies comes with many analytical challenges: high number of candidate biomarkers measured compared to the number of patients, correlations across biomarkers leading to computational challenges. Computationally efficient and powerful quantitative methods addressing the complexity of new data are needed. With the increasing complexity of study designs within the pharmaceutical and biotechnological research disciplines, the partner organization will gain additional expertise and insight with future statistical analysis tasks.

Faculty Supervisor:

Irina Dinu

Student:

Partner:

Applied Pharmaceutical Innovation

Discipline:

Life Sciences

Sector:

Professional, scientific and technical services; Retail trade

University:

University of Alberta

Program: