EdX

Demystifying Biomedical Big Data: A User’s Guide (edX)

Demystifying Biomedical Big Data: A User’s Guide (edX)

Whether you are a student, basic scientist, researcher, clinician, or librarian, this course is designed to help you understand, analyze, and interpret biomedical big data.

Class Deals by MOOC List - Click here and see EdX's Active Discounts, Deals, and Promo Codes.

With the continuous generation of massive amounts of biomedical data on a daily basis, whether from research laboratories or clinical labs, we need to improve our ability to understand and analyze the data in order to take full advantage of its power in scientific discoveries and patient care. For non-bioinformaticians, “handling” big data remains a daunting task. This course was designed to facilitate the understanding, analysis, and interpretation of biomedical big data to those in the biomedical field with limited or no significant experience in bioinformatics. The goal of this course is to “demystify” the process of analyzing biomedical big data through a series of lectures and online hands-on training sessions and demos. You will learn how to use publicly available online resources and tools for genomic, transcriptomic, and proteomic data analysis, as well as other analytic tools and online resources. This course is funded by a research grant from the US National Institutes of Health (NIH)-Big Data to Knowledge (BD2K) Initiative.

What you'll learn

  • Understand how biomedical data are being generated and processed
  • Learn about various biomedical big data resources (e.g. TCGA, G-DOC, UNIPROT, etc.)
  • Explore and analyze genomic, transcriptomic, and proteomic data using various online analysis tools
  • Make sense of big data using systems biology resources and tools
  • Appreciate the value of big data in biomedical research and clinical practice (e.g. enabling precision medicine)

Course Syllabus

Week 1: Introduction and Overview of Bioinformatics Platforms and Resources
-Introduction to the Course -Interview with Bioinformatics at Georgetown University Medical Center. Dr. Robert Clarke, Dean for Research, at Georgetown University Medical Center
-Biomedical Informatics: Enabling Research and Health Care. Interview with Dr. Subha Madhavan, Director of the Innovation Center for Biomedical Informatics (ICBI) at Georgetown University
-Biomedical Big Data: Enabling Personalized Medicine. Interview with Dr. John Marshall, Chief, Hematology and Oncology, Lombardi Comprehensive Cancer Center, Georgetown University Medical Center internationally recognized medical oncologist

Week 2: Translational Research and Big Data
Translational Research
Translational Research Lecture, Part 1 Part I
Translational Research Lecture, Part 2 Part II
The Cancer Genome Atlas
The Cancer Genome Atlas Lecture
The Cancer Genome Atlas Demo
The Cancer Genome Atlas Exercise
Introduction to G-DOC
G-DOC Lecture
G-DOC Demo
G-DOC Exercise

Week 3: DNA and Big Data
DNA Copy Number
DNA Copy Number Lecture
DNA Copy Number Demo
DNA Copy Number Exercise
Genome Sequencing
Genome Sequencing Lecture, Part 1
Genome Sequencing Lecture, Part 2
Genome Sequencing Demo
Genome Sequencing Exercise

Week 4: RNA and Big Data
Gene Expression
Gene Expression Lecture
Gene Expression Demo
Gene Expression Exercise
MicroRNA
MicroRNA Lecture
MicroRNA Demo
MicroRNA Exercise

Week 5: Proteins and Big Data Part I
Proteomics
Protein Sequences Lecture
Protein Interactions Lecture
Mass Spec Proteomics, Lecture
Proteomics Exercise

Week 6: Proteins and Big Data Part II
Proteomics (Continued)
Data Sharing, Metadata, Data Formats
Ontologies
Proteomics Demo, Part 1
Proteomics Demo, Part 2
Proteomics Demo, Part 3
Proteomics Exercise

Week 7: Systems Biology and Big Data
Systems Biology
Systems Biology Lecture, Part 1
Systems Biology Lecture, Part 2
Systems Biology and Data Analysis Demo
Systems Biology Exercise

Week 8: Perspectives from the Field and Course Conclusion
Perspectives from the Field
-Regulatory issues Issues related Related to biomedical Biomedical big Big dataData. Sheila Zimmet, JD, Senior Associate Vice President for Regulatory Affairs, and Ashley Carver, JD, Deputy Conflicts Officer and Regulatory Affairs Associate, Georgetown University Medical Center.
-Enabling Everyone to Share and Use Public Datasets. Interview with Dr. Ben Busby, genomics Genomics outreach Outreach coordinator Coordinator at the National Center for Biotechnology Information (NCBI)
-Interview withCancer Moonshot. Dr. Jerry Lee, Deputy Director, Center for Strategic Scientific Initiatives, Office of the Director, National Cancer Institute, National Institutes of Health

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Analyzing Data with R (edX) EdX
IBM

Analyzing Data with R (edX)

R is the key that opens the door between the problems you want to solve with data and the answers you need. This course walks you through the process of answering questions through data. The R programming language is purpose-built for data analysis. R is the key that opens the door between the problems you want to solve with data and the answers you need to meet your objectives.

Self Paced
Self-Paced
Programming for Data Science (edX) EdX
University of Adelaide,AdelaideX

Programming for Data Science (edX)

Learn how to apply fundamental programming concepts, computational thinking and data analysis techniques to solve real-world data science problems. There is a rising demand for people with the skills to work with Big Data sets and this course can start you on your journey through our Big Data MicroMasters program towards a recognised credential in this highly competitive area. Using practical activities you will learn how digital technologies work and will develop your coding skills through engaging and collaborative assignments.

Self Paced
Self-Paced
Técnicas Cuantitativas y Cualitativas para la Investigación (edX) EdX
Universitat Politècnica de València,UPValenciaX

Técnicas Cuantitativas y Cualitativas para la Investigación (edX)

El curso pretende acercar al alumno al método científico y, en concreto, cómo éste se aplica al estudio y análisis de los métodos de casos. El curso que se propone es ideal para investigadores y alumnos que se encuentren cursando trabajos de fin de grado, trabajos de fin de máster o realizando tesis, así como todos aquellos del área de la administración que quieran realizar un análisis cuantitativo o cualitativo en sus estudios.

Self Paced
Self-Paced
Introduction to Management Information Systems (MIS): A Survival Guide (edX) EdX
Universidad Carlos III de Madrid - UC3M,UC3Mx

Introduction to Management Information Systems (MIS): A Survival Guide (edX)

Gain the skills and knowledge needed to succeed in an MIS-dominated corporate world. This MIS course will cover supporting tech infrastructures (Cloud, Databases, Big Data), the MIS development/ procurement process, and the main integrated systems, ERPs, such as SAP®, Oracle® or Microsoft Dynamics Navision®, as well as their relationship with Business Process Redesign.

Self Paced
Self-Paced
Data Science: Inference and Modeling (edX) EdX
HarvardX,Harvard University

Data Science: Inference and Modeling (edX)

Learn inference and modeling, two of the most widely used statistical tools in data analysis. Statistical inference and modeling are indispensable for analyzing data affected by chance, and thus essential for data scientists. In this course, you will learn these key concepts through a motivating case study on election forecasting.

Self Paced
Self-Paced
Data Science: Capstone (edX) EdX
HarvardX,Harvard University

Data Science: Capstone (edX)

Show what you’ve learned from the Professional Certificate Program in Data Science. To become an expert data scientist you need practice and experience. By completing this capstone project you will get an opportunity to apply the knowledge and skills in R data analysis that you have gained throughout the series. This final project will test your skills in data visualization, probability, inference and modeling, data wrangling, data organization, regression, and machine learning.

Self Paced
Self-Paced
Introduction to Digital Humanities (edX) EdX
HarvardX,Harvard University

Introduction to Digital Humanities (edX)

Develop skills in digital research and visualization techniques across subjects and fields within the humanities. This course will show you how to manage the many aspects of digital humanities research and scholarship. Whether you are a student or scholar, librarian or archivist, museum curator or public historian — or just plain curious — this course will help you bring your area of study or interest to new life using digital tools.

Self Paced
Self-Paced
High-Dimensional Data Analysis (edX) EdX
HarvardX,Harvard University

High-Dimensional Data Analysis (edX)

A focus on several techniques that are widely used in the analysis of high-dimensional data. If you’re interested in data analysis and interpretation, then this is the data science course for you. We start by learning the mathematical definition of distance and use this to motivate the use of the singular value decomposition (SVD) for dimension reduction and multi-dimensional scaling and its connection to principle component analysis.

Self Paced
Self-Paced
Statistics and R (edX) EdX
HarvardX,Harvard University

Statistics and R (edX)

An introduction to basic statistical concepts and R programming skills necessary for analyzing data in the life sciences. We will learn the basics of statistical inference in order to understand and compute p-values and confidence intervals, all while analyzing data with R. We provide R programming examples in a way that will help make the connection between concepts and implementation.

Self Paced
Self-Paced
Data Processing and Analysis with Excel (edX) EdX
Rochester Institute of Technology,RITx

Data Processing and Analysis with Excel (edX)

Learn to use Excel to organize and clean data so it can be manipulated and analyzed. In this course, you will learn how to organize your data within the Microsoft Office Excel software tool. Once organized, we will discuss data cleaning. You will learn how to identify outliers and anomalies in the data, and how to identify and change data-types. Together we will develop a data analysis plan, after which we will apply analysis methods and tools, including exploratory analysis, evaluation of results, and comparison with other findings.

Self Paced
Self-Paced
Big Data, Hadoop, and Spark Basics (edX) EdX
IBM

Big Data, Hadoop, and Spark Basics (edX)

This course provides foundational big data practitioner knowledge and analytical skills using popular big data tools, including Hadoop and Spark. Learn and practice your big data skills hands-on. Organizations need skilled, forward-thinking Big Data practitioners who can apply their business and technical skills to unstructured data such as tweets, posts, pictures, audio files, videos, sensor data, and satellite imagery, and more, to identify behaviors and preferences of prospects, clients, competitors, and others. ****

Self Paced
Self-Paced
Analyzing and Visualizing Data with Power BI (edX) EdX
Davidson College,DavidsonX

Analyzing and Visualizing Data with Power BI (edX)

Step up your analytics game and learn one of the most in-demand job skills in the United States. Power BI is a robust business analytics and visualization tool from Microsoft that helps data professionals bring their data to life and tell more meaningful stores. This four-week course is a beginner's guide to working with data in Power BI and is perfect for professionals. You'll become confident in working with data, creating data visualizations, and preparing reports and dashboards.

Self Paced
Self-Paced