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Translational Biomedical Informatics

Course Information

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

Core Lecture Courses (Required, 24 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 focused on how researchers can use existing tools together to explore novel biomedical questions in ways that retain reproducibility. This course is to insure all students 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.

    This course is a core requirement, but may be substituted with INF 549 Introduction to Computational Thinking and Data Science with prior permission

  • This course is part one of a two-course series and complements courses offered as part of masters 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.

    This course is a core requirement

  • This course is part two of a two-course series and complements courses offered as part of masters 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 fundamentals of genomics, transcriptomics, proteomics and epigenomics technologies and will learn how their application and use drives analytical problems. Students will be expected to be familiar with and now experienced with many foundational skillsets introduced in earlier courses that are necessary in biomedical informatics. This course continues to build those by reinforcement with increased focus on timeliness and flexibility within more complex analysis.

    This course is a core requirement

  • The objective of this course is to provide advanced bioinformatic training in 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 where in 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 focus are the current standards and key resources in human annotation and gene ontology.

    This course is a core requirement, but may be substituted with INF 550 Overview of Data Informatics in Large Data Environment with prior permission

  • 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 the foundational understanding of modern molecular genetic technologies and the evolution to next-generation technologies. At its core, this course teaches principles of conducting large-scale data analysis and appreciating how the nature and type of data impacts 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.

  • 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 individuals 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

  • This course will provide students the opportunity to build a portfolio in the form of a web-based application that can captures 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 units)

  • TGRN 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