USC's Department of Translational Genomics is offering an intensive two-year MS program in bioinformatics/biomedical informatics. This program is focused on training individuals who have strong backgrounds in laboratory-based biomedical sciences and seek the skills for analyzing, processing, and managing large-scale data. Graduates will be suited to work as applied bioinformaticians within academic research laboratories, clinical research laboratories, pharmaceutical companies, and biotechnology companies.
April 1st, 2018. Application Deadline
August 17th 2018. Orientation
August 20th, 2018. Classes Begin
WHAT IS TRANSLATIONAL BIOMEDICAL INFORMATICS?
Masters In Translational Biomedical Informatics is to train applied bioinformaticians, providing students with the the training, skillsets, and best practices for applying and integrating existing bioinformatics tools in the study of human health and disease.
Translational: Translating laboratory data to bedside or clinic Biomedical: Relating to human biology, medicine, and disease Informatics: Applied processing and analysis of data
This program is tailored for individuals with laboratory-based biomedical experience and whom have bachelors in biomedical sciences or biomedical engineering. This program focuses on tool application and integration along pipelines, will scripting emphasized over coding. Graduates will have the analytical capabilities for analyzing datasets across molecular biology, systems biology, structural biology, and genomic sequencing datasets. A major emphasis is on data analysis and data processing associated with next-generation sequencing (NGS) data, understanding that the goal is to build core skillsets that remain relevant as new technologies emerge and change.
STUDENTS IN THIS PROGRAM WILL GAIN AN UNDERSTANDING OF:
- Best practices for putting existing tools and informatics datasets together to better understand biomedical problems; Analysis of next-generation sequencing (NGS) including whole-genome, exome, and transcriptome sequencing (RNA-seq), as well as emerging methods in single-cell sequencing; Project management and requirements gathering skills to allow them to interface and interact with computational and engineering expertise to help design solutions; Experience and training utilizing modern frameworks for rapid prototyping, and how to extract information from a wide variety of databases; Core responsibilities towards data security, privacy, and data sharing spanning open access frameworks to restricted and regulated frameworks;
LEARN SCRIPTING CODING FOR BIOMEDICAL DATA ANALYSIS
WHAT IS THE LEARNING ENVIRONMENT LIKE?
This program uses both traditional class-room based teaching, an applied in silico laboratory for assignments that is coupled with additional on-line materials. Bioinformatics after all is about working mostly on computers with a community that spans the world for help. Within the program each class varies.
Most courses alternate between online interactions with faculty followed by in-class lectures and laboratories. Class is often focused on helping students apply concepts that were made available outside of the classroom. Fundamentally, this is an applied program where the focus is on learning to become independent and solve new problems as they emerge. It teaches processes, though in a way that is effectively learning by example. For example, several courses have a strong inclusion of R, R-markdown, and R-shiny, where students develop web-applications to complete homework by submission via GitHub. These applications may include a biomedical research or clinical problem commonly seen in the field. Classroom time is often used for working with teams of students on their solutions and suggesting paths through obstacles. In person classes are often interactive with students and lectures engaged in ongoing dialogue where lecture materials were already made available and reviewed prior to the course. Students who succeed use both online resources and the in-person classroom time.