The Galaxy Platform for Accessible, Reproducible, and Scalable Biomedical Data Science

February 11, 2022 3:00 p.m. - 4:00 p.m. ET

Dr. Jeremy Goecks will share how cancer researchers are using the machine learning capabilities of the Galaxy project, one of the largest and most widely used open-source platforms for biomedical data science, to predict therapeutic responses and analyze tumor spatial biology. In addition to Galaxy’s machine learning functions, cancer researchers can use it to access cutting-edge analysis methods, reproduce and share complex computational analyses, and perform large-scale analyses across many data sets. Dr. Goecks will also discuss how NCI’s Human Tumor Atlas Network—a series of open-source atlases showing the 3-dimensional cellular, morphological, and molecular features of human cancers—can be used in conjunction with Galaxy.

This webinar is part of the monthly Containers and Workflows Interest Group (CWIG) webinar series. CWIG brings together data scientists, bioinformaticians, computer scientists, and researchers to learn more about cloud computing and container technologies, workflows, and pipelines that could drive cancer data science.

The webinar series features a variety of presenters from across NIH, industry, and academia. Though cancer research is the focus of the series, unrelated data science and cloud computing topics are still welcome. In the last year, the CWIG webinar speakers have discussed:

  • NIH cloud programs like the Cancer Genomics Cloud (CGC), its fellow NCI Cloud Resources, and NIH Science and Technology Research Infrastructure for Discovery, Experimentation, and Sustainability (STRIDES).
  • commercial cloud platforms for biomedical data storage and computing.
  • pipelines and tools for deep learning and various omics analysis.
Jeremy Goecks, Ph.D.

Dr. Goecks is an associate professor of biomedical engineering and section head for Cancer Data Science at Oregon Health & Science University. He is also a principal investigator for the NCI Cancer MoonshotSM Center in the Human Tumor Atlas Network (HTAN) and the Galaxy platform.

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