Students will learn the basic concepts, technology, and processes that guide the practical use of common statistical methods. The course introduces descriptive and inferential statistics and applications to real-world data. Students will reinforce learning with problem sets, a publicly sharable R portfolio, and a final project to achieve practical competence in the use of statistical software and interpretation of results.

The course will expand students' statistical programming skills to utilize disparate datasets to generate conclusions about complex questions. Students will reinforce learning with problem sets and assignments to achieve competence in the use of statistical software to clean and organize data and apply the correct statistical approach (ANOVA, Chi-Square, regression, multiple regression) to interpret results.

The Translational Science Course is designed to prepare graduate students to engage in cutting-edge basic science discovery; understand proof-of-concept research and industrial designed experiments; innovate and invent; create valuable intellectual properties; optimize patent enablements and claims; interact with regulatory agencies; champion entrepreneurship and commercialization activities; and enhance societal impact of basic research.

Students will learn theoretical and practical foundations of computational methods for analysis of experimental data from various biological data types. Course will cover algorithms, statistical and computational methods, and application areas in computational biology, and will include both classical methods as well as recent advances. Prior coursework/experience in linear algebra, UNIX, and R & Python programming required.

Students will continue study in more advanced areas of computational biology, covering more advanced models, algorithms, and computational methods as applied to a variety of biological data types. Students will study theory and practice of machine learning methods commonly used in biology and implement and apply these models in various areas of biology.

This course is for visiting research students participating in the BIMS Visiting Research Graduate Trianeeship Program (VRGTP). Students in this course are dual enrolled in their home institution and will participate in research for a minimum of 4 semesters. The research will assist them in completing their degree at their home institution. Non-degree students.

This course introduces students to biomedical research. Students conduct one or more research projects of limited scope under the direction of faculty and lab members. It is open only to graduate students in Biomedical Sciences (BIMS).

Preparation for Doctoral Research prior to completion of candidacy examination.

For doctoral dissertation following advancement to PhD candidacy.