Bioinformatics

Masters In Translational Biomedical Informatics

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TRANSLATIONAL BIOMEDICAL INFORMATICS - PROGRAM SUMMARY

Overview

USC's Department of Translational Genomics at Keck's School of Medicine is offering an intensive two-year MS program in biomedical informatics focusing on bioinformatics within health-related fields.  This program is focused on training individuals who have strong backgrounds in laboratory-based biomedical sciences and seek the bioinformatic 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.

What is Translational Biomedical Informatics?

The goal of this program is to train applied bioinformaticians, providing students with 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, biomedical sciences, or biomedical engineering. This program focuses on tool application and integration along pipelines, will scripting emphasized over coding. Students with laboratory experienced will be prioritized. It is not a program intended for medical or clinical professionals.

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 skill sets that remain relevant as new technologies emerge and change.

Learning Objectives (Download)

Upon graduation, students will:

  • Understand best practices for putting existing tools and bioinformatics datasets together to better understand biomedical problems;
  • Be able to analyze next-generation sequencing (NGS) including whole-genome, exome, and transcriptome sequencing (RNA-seq), as well as emerging methods in single-cell sequencing;
  • Understand project management and requirements in bioinformatics gathering skills to allow them to interface and interact with computational and engineering expertise to help design solutions;
  • Have experience and training utilizing modern frameworks for rapid prototyping, and how to extract information from a wide variety of databases;
  • Understand core responsibilities towards data security, privacy, and data sharing spanning open access frameworks to restricted and regulated frameworks;
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LEARN NEXT GENERATION SEQUENCING ANALYSIS

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What is the learning environment like?

This program uses both traditional classroom-based teaching and applied in-silico laboratory for assignments that are coupled with additional online 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.  The 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 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 an ongoing dialogue where lecture materials were already made available and reviewed prior to the course.  Students who succeed use both online resources and in-person classroom time.

How does this program compare with computational biology or Ph.D. programs?

This is a critical differentiator and one that is behind the tremendous need for master's level bioinformaticians.

First, one must understand what this program is not.  It is not a program that teaches theory and also on the development of new tools to solve biomedical problems. This area is best described as computational biology and many great Ph.D. programs serve this area.   For example, computational biologists may develop a new alignment tool. They require strong algorithmic and software engineering foundations.  There are many tremendous programs that serve this area - and many at USC.

Master's level bioinformaticians focus on applying or building from existing tools to biomedical problems. They uniquely understand both the scope and types of bioinformatics tools available and are often linking together different tools into frameworks, platforms, and pipelines. They understand the context of the biomedical problem faced by their team members, often because they were in the laboratory and have a good appreciation for disease or clinical care.  Very simply, bioinformaticians are applied and are able to adapt and put different tools together, preferring existing, established, and validated frameworks.  They focus on quality control and best-practices and find themselves more often in applied settings working with real patient data or building frameworks that impact directly human health and disease.  Frameworks built by bioinformaticians are typically specific for a groups use, and go well beyond simple running software, but do take a deep understanding of how these tools are made, validated, and versioned.  Bioinformaticians know and understand the rules and regulations for managing data relating to human subjects - both in research and in the clinical care stream.

COURSES

Course Information (28 Units Total)

General requirements include at least 28 units of required courses as follows:

Core Lecture Courses (Required: 24 Units)

TRGN-510. Basic Foundations in Translational Biomedical Informatics (4 Units).

The goal of this introductory platform course is to teach core fundamentals that will allow a someone trained in biology or medicine how to use modern computing and bioinformatics tools to rapidly and reproducibly answer biological questions within an applied setting. The focus is significant on how researchers can use existing tools together to explore novel biomedical questions in ways that retain reproducibility. This course is for all students to have the core fundamentals for the rest of the program and will have bridge together courses that form the Masters in Translational Biomedical Informatics program.  Please be aware the students are expected to have a Mac laptop with Sierra or later operating system installed for enrollment.

This course is a core requirement but may be substituted with INF 510 Principles of Programming for Informatics.  The INF510 course provides a more focused training specific to python whereas the TRGN510 focuses more on the use of R, bash, and other scripting languages including python in the context of biomedical applications.  For more information on INF510, please see https://classes.usc.edu/term-20161/course/inf-510/

TRGN-514. Introduction to Human Genomic Analysis Methods (4 Units).

This course is part of a two-course series and complements courses offered as part of a master's in biomedical informatics.  This course is necessary to both teach modern genomics analysis, but to provide students with the broader skillset to adapt and grow in the field as technologies change.  More than most fields, they will frequently change tools and frequently build single-use solutions. This course will focus on implementing, versioning, best practices, planning, and delivery specific to translational research by example using a series of emerging methodologies. Please be aware the students are expected to have a Mac laptop with Sierra or later operating system installed for enrollment.

This course is a core requirement

TRGN-515. Advanced Human Genomic Analysis Methods (4 Units).

This course is part two of a two-course series and complements courses offered as part of a master's in biomedical informatics. This course will continue the process of both teaching modern genomics analysis while providing students with the broader skillset to adapt and grow in the field as technologies change. Students will learn the fundamentals of genomics, transcriptomics, proteomics, and epigenomics technologies and will learn how their application and use drive analytical problems. Students will be expected to be familiar with and now experienced with many foundational skillsets introduced in earlier courses that are necessary for biomedical informatics. This course continues to build those by reinforcement with an increased focus on timeliness and flexibility within the more complex analysis. Please be aware the students are expected to have a Mac laptop with Sierra or later operating system installed for enrollment.

This course is a core requirement

TRGN-516.  Translational Genomics, Applied Databases and Data Structures (4 Units)

The objective of this course is to provide advanced bioinformatics training in the use of databases and development of databases for sharing results and tracking information. The course will cover how to work with databases and understanding the regulatory environment around their use. A major part of this course will be on applied projects wherein teams students will be asked to use a case-study based approach to identify appropriate datasets, use analytic tools to analyze data, evaluating hypotheses, and interpret results. The first major foci are the current standards and key resources in human annotation and gene ontology. Please be aware the students are expected to have a Mac laptop with Sierra or later operating system installed for enrollment.

This course is a core requirement but may be substituted with INF 550 Overview of Data Informatics in Large Data Environment with prior permission.  The TRGN516 course is focused on biomedical applications and the management of biomedical data, particularly within a healthcare context.  INF550 provides a deeper technical view using applications that are much broader.  In that context, TRGN has a narrower focus on healthcare applications and the associated regulated frameworks, whereas INF550 provides a deeper technical basis within databases and data structures.

TRGN-524.  Applications of Genomic Technology in Biomedical Research I (4 Units)

This course is an introductory level course and necessary for Masters of Science (MS) degrees in both Biomedical Informatics and Translational Biotechnology. This course is necessary to build a foundational understanding of modern molecular genetic technologies and the evolution of next-generation technologies. At its core, this course teaches the principles of conducting large-scale data analysis and appreciating how the nature and type of data impact the analysis approach. Next-generation sequencing data is at its nature pseudo-single molecule and analysis approaches treat error differently, and this has implications towards interpretation.  Through these courses, students will understand the inherent challenges and opportunities by bridging analysis together to uncover new discoveries, through integration across genomics, transcriptomics, proteomics and epigenomics technologies.  Students will learn how these tools are developed and how they are impacting both the laboratory and the clinical setting.  Through this course, students will also learn how biotechnology leads to commercialization and gain an understanding of governmental regulations and ethics surrounding hot topic issues such as cloning, stem cells, and genome sequencing.

TRGN-525. Applications of Genomic Technology in Biomedical Research II

This is the second of two courses with the objective to train and provide individuals with strong backgrounds and interests in biological or medical sciences the theoretical and applied knowledge of modern-day biotechnology. It will introduce students to tools and applications that will be instrumental throughout the Biomedical Bioinformatics and Translational Biotechnology Masters programs. This course targets those who have some previous training in biomedical sciences, and aims to provide them with the foundations, basic principles, and core concepts in biotechnology and its applications to basic science, health, and disease. Students will learn how biotechnology leads to commercialization and gain an understanding of governmental regulations and ethics surrounding hot topic issues such as cloning, stem cells, and genome sequencing.

This course is a recommended elective, but may be substituted for one of the electives below

TRGN-520. Translational Biomedical Informatics Capstone Portfolio

This course will provide students the opportunity to build a portfolio in the form of a web-based application that can capture the projects developed and completed through this course, and also show-cases one larger cap-stone project. The overall objective is to provide students provides the culminating, integrative curricular experience and an overarching project tailored to the career direction they are targeting and build a reactive widely accessible “WebApp” that showcases their project.

Electives (At Least 4)

  • TRGN 525. Foundations, Concepts, Core Principles In Biotechnology II
  • PM 570 Statistical Methods in Human Genetics.
  • PM 538 Introduction to Biomedical Informatics.
  • BME 528 Medical Diagnostics, Therapeutics and Informatics.
  • PM 570 Statistical Methods in Human Genetics.
  • INF 510 Principles of Programming for Informatics.
  • INF 550 Overview of Data Informatics in Large Data Environments.
  • NIIN 500 Neuroimaging and Systems Neuroscience.
  • NIIN 540 Neuroimaging Data Processing Methods.

Applied Learning Of High Performance Computer, Management of Large Scale Biomedical Data

ADMISSION

Admission requirements include a minimum GPA of 3.0 and an undergraduate major in biological sciences, or at least 6 bioscience courses in the molecular, cellular, genetics and biochemistry topics.

Formal application via USC Office of Graduate Admission’s online portal is required.

  • Completed online application.
  • Statement of purpose (approximately 500 words): Tell us where you came from, where you are going to, and how enrolling in the Translational Biotechnology Program may help you reach your academic or career goals.
  • Resume or CV: There is no specific format requirement for Resume or CV.
  • Letters of recommendation (minimum three): We accept letters from both academic and professional evaluators.  At least two of the letters should address your bioscience aptitude.   All letters must be on the letterhead of the organization or department.
  • Transcripts from ALL previously attended post-secondary institutions regardless of whether a degree was obtained. This program is not intended for medical professionals who actively are involved in clinical care.
  • International students whose first language is not English are required to provide evidence of English Proficiency: TOEFL (iBT) 90, with no less than 20 on each section, or IELTS 6.5, with 6 or above on each band.
  • Students with strong bioscience preparation but with lower language proficiency scores could consider applying to USC’s International Academy Pre-master’s programs.

RESOURCES

Cost of Attendance and Financial Aid

Estimated budgets for tuition, fees, books, supplies, room, board and other living expenses can be found here.  Tuition is charged at the same rate for both in-state and out-of-state residents.

Students may apply for financial aid through USC Financial Aid Office, which provides additional information for federally backed student loans, private financing and federal work-study program.  Limited funding opportunities can be found at the Office of Academic Honors and Fellowships and USC Graduate School.

USC OFFICE OF INTERNATIONAL SERVICES

The Office of International Services (OIS) provides continuing support services for international students. Professionally trained counselors and student peer counselors are available to advise international students on important issues such as immigration regulations, academic progress, financial concerns, housing and cross-cultural adjustment. Through this office, students can receive information about social and cultural activities.

CONTACT

MS Translational Biomedical Informatics 
Keck School of Medicine of USC
1975 Zonal Avenue, KAM 409
Los Angeles, CA 90033

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For additional information or questions, please contact

Program Director
David W. Craig, Ph.D.
Email: davidwcr@usc.edu