Biomedical Sciences

This course is designed to equip students with core concepts and fundamental skill sets needed for biomedical research. It combines traditional didactic lectures with small group and individual learning activities, problem solving exercises, workshops, and hands-on analyses of data sets. The course emphasizes the integration of topics spanning the fields of biochemistry, cell and molecular biology, and genetics.

Beginning in 1989, the National Institutes of Health introduced a requirement that institutions provide a program of instruction in the responsible conduct of research (NIH Guide for Grants and Contracts, Volume 18, Number 45, 1989). This was later expanded to require that all fellows on NIH training grants should receive instruction in the responsible conduct of research. The requirement does not specify a particular format or curriculum. However, recommendations are made that several areas should be covered in the instruction: conflict of interest, responsible authorship, policies for handling misconduct, policies regarding the use of human and animal subjects, and data management. This course is designed to help student consider each of these areas and therein formulate an understanding of responsible conduct in research.

Each week, a UVA faculty member or guest lecturer will summarize current work in their area of research. The emphasis in these lectures will be on high-throughput genomic and bio-informatic approaches to elucidating the mechanisms of pathogenesis in human disease and disease models.

The course will cover human genetics and genomics, including the human/mammalian genome variation, determination of genomic variation on phenotype and disease risk, mapping and characterizing genetic variants on phenotype, determining the putative impact of genetic variants on gene expression (transcriptomics, epigenomics), the promise and implications of genome science on precision medicine and the ethical, legal & social implications.

This course will provide an overview of the practice of science itself and the basis for claims of scientific knowledge, by integrating advances from philosophy, psychology, history, sociology, and anthropology into a holistic view. Students will acquire an advanced understanding of what science is and how it really works - providing them with a necessary intellectual toolbox to carry out science of their own and evaluate science of others.

This second course focuses on generating data with common biological techniques and understanding the foibles of observation, assay development and scrutiny, and the effects of instrumentation.

CVRC Seminars

A series of joint lectures by basic and clinical scientists that focus on the clinical context of a specific biomedical problem and the contemporary research that has resulted in major advances and treatment of the disease. Students participate in workshops on grantsmanship with coincident feedback on student's specific aims from faculty experts.

A series of joint lectures by basic and clinical scientists that focus on the clinical context of a specific biomedical problem and the contemporary research that has resulted in major advances and treatment of the disease.

The Research in Progress Colloquium is a series of research seminars and short talks by students in our combined M.D./Ph.D. Program. The major goals of the course are to familiarize students with key research areas of importance for training as physician scientists, and to develop the student's presentation skills. Students are required to give a minimum of one oral presentation per year to their fellow students and to selected faculty members who have expertise in the area of presentation. Students also are required to attend presentations of other students and to participate in group discussions. In addition to research presentations by students, there will also be presentations by faculty members in areas of significance for training of physician scientists. Grading (S/U) will be based on the quality of the students' presentation, as well as the extent of their participation in group discussions.

The Research in Progress Colloquium is a series of research seminars and short talks by students in our combined M.D./Ph.D. Program. The major goals of the course are to familiarize students with key research areas of importance for training as physician scientists, and to develop the student's presentation skills. Students are required to give a minimum of one oral presentation per year to their fellow students and to selected faculty members who have expertise in the area of presentation. Students also are required to attend presentations of other students and to participate in group discussions. In addition to research presentations by students, there will also be presentations by faculty members in areas of significance for training of physician scientists. Grading (S/U) will be based on the quality of the students' presentation, as well as the extent of their participation in group discussions.

A two to three month training experience at a biotechnology or pharmaceutical company. BTP or non-BTP students contribute to host company research projects, offer ideas and interact with company officials. Student performance is graded by the hosting company official using a standardized form (http://www.surveygizmo.com/s3/1742633/UVa-Biotech-Externship-Evaluation). Externship occurs within 2 years of entering the BTP.

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 foundational computational methods for analysis of data from genome, epigenome, and transcriptome sequencing experiments. The course will cover various biological data types, algorithms, statistical and computational methods, and application areas in genomics and systems biology. Prior coursework/experience in linear algebra, UNIX, and R and Python programming required.

This course will cover fundamental topics in statistical genetics with a focus on concepts and methods critical to a concrete understanding of the application of statistical genetics to public health genomics. Major topics covered in this course include modes of genetic inheritance, heritability analysis, linkage and association mapping, integrative analysis leveraging molecular 'omics' data, and genetic risk prediction modeling.

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.

Navigating graduate school, the career exploration process, research environments, and the stress of life can seem overwhelming and lead us to doubt ourselves just when we need confidence the most. The goal of this course is to help students develop the tools for resilience that they need to navigate challenging situations in school, work, and life.

Students will conduct a research project where they learn how to apply computational/ bioinformatic tools to study globally prominent microbial pathogens. Experts on the topic provide guidance and feedback. It is required of all trainees in the Global Biothreats Training Program. Topics include identifying and predicting microbial variants and virulence factors, and modeling epidemic spread through a population of differing susceptibilities.

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.