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  • BDSI 8000: Biomed Data Sci & Info Seminar

    1.00 Credits
    Clemson University

    Exposes students to a broad range of concepts, theories, methods, and practices in biomedical data science and informatics, and the specific research topics pursued by the faculty in the program. Students learn to comprehend and present scientific literature in the field. To be taken Pass/No Pass only. May be repeated for a maximum of four credits. Preq: Enrollment in the Biomedical Data Science and Informatics PhD program or consent of instructor.
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  • BDSI 8010: Intro to Biomed Informatics

    3.00 Credits
    Clemson University

    This course provides an overview of the biomedical informatics field. Students learn fundamental theories and concepts of bioinformatics, clinical research informatics, health informatics, consumer health informatics, and public health informatics, and how informatics tools, techniques, and approaches are used to support research and health care.
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  • BDSI 8020: Biomed Data Standards/Terminol

    3.00 Credits
    Clemson University

    This course introduces data science and informatics students, clinicians, and public health practitioners to fundamental principles of data standards and terminologies and their importance for exchange and meaningful use of health data and information. Preq: BDSI 8010.
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  • BDSI 8110: Precision Medicine Informatics

    3.00 Credits
    Clemson University

    Precision Medicine Informatics is the discovery of individualized treatments through the integration of biologic and behavioral data with the goal of providing better care to the individual. This course provides an overview of precision medicine informatics with a focus on cancer. It covers current initiatives and efforts to use health informatics to individualize care. The integration of heterogeneous data sets from different measurements such as the exposome, metabolome, genome, proteome, and other laboratory measurements is central to the goal of treating each patient as an individual in regard to precision treatment. As a use case, students do a detailed examination of precision medicine clinical trials in cancer. They also examine publicly available data to understand how high throughput measurement techniques are used and the methods that are applied to them to more precisely characterize cohorts of patients. Preq: BDSI 8010.
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  • BDSI 8120: Clin/Translational Informatics

    3.00 Credits
    Clemson University

    This course provides an overview of clinical and translational research informatics. Students learn about research data management, relational database design, modern research data capture tools, best practices, clinical data warehousing, security risks and mitigations, privacy issues in electronic data, data standards, data mining and other related topics. Students get hands-on experience using modern translational research informatics tools such as REDCap, i2b2 and others.
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  • BDSI 8210: Machine Learning for Biomed

    3.00 Credits
    Clemson University

    This course provides an introduction to methods in statistical learning commonly used to extract important patterns and information from biomedical data. Topics include linear methods for regression and classification, regularization, kernel smoothing methods, statistical model assessment and selection, and support vector machines. Unsupervised learning techniques such as principal component analysis and generalized principal component analysis are also discussed. The topics and their applications are illustrated using the statistical programing language R. Preq: STAT 8010.
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  • BDSI 8310: Microbiome Informatics

    2.00 Credits
    Clemson University

    This course is concerned with analysis of microbiome data enabled by high-throughput sequencing technologies. It briefly covers foundational concepts in microbial ecology, molecular biology, bioinformatics, and DNA sequencing. The main focus of the course is on developing an understanding of multivariate analysis of microbiome data. Practical skills developed in this course include managing high-dimensional and structured data in metagenomics, visualization and representation of high-dimensional data, normalization, filtering, and mixture-model noise modeling of count data, as well as clustering and predictive model building.
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  • BE 1990: Creative Inquiry I

    1.00 Credits
    Clemson University

    In consultation with and under the direction of a faculty member, students pursue scholarly activities individually or in teams. These creative inquiry projects may be interdisciplinary. Arrangements with mentors must be established prior to registration. May be taken twice for a maximum of six credits. To be taken Pass/No Pass only.
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  • BE 2100: Intro to Biosystems Engr

    2.00 Credits
    Clemson University

    Overview of topics and engineering application areas that comprise the biosystems engineering profession. Significant emphasis is also given to development of oral and written communication skills needed by the engineering professional, introduction to design methodology, and application of engineering fundamentals to biological systems. Preq: ENGR 1020; and either MATH 1060 or MATH 1070. Coreq: BE 2101.
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  • BE 2101: Intro to B E Lab

    0.00 Credits
    Clemson University

    Non-credit laboratory to accompany BE 2100. Coreq: BE 2100.
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