Keynote Speaker: Christopher A. Longhurst, MD, MS
"Big Data" is an overhyped term in biomedicine. In this talk, Dr. Longhurst will share some real-world examples of the value realized by bringing big data to the bedside in both clinical research at Stanford and commercial startups in the Silicon Valley.
The computational and statistical toolkit for quantitative analysis of large data sets is developing rapidly, partly through the focus on “Big Data”.
The successful application of informatics requires understanding of data, technology and the unique needs of the beneficiary, whether the consumer of food products or a critically ill patient.
Images are used to store vast amounts of biological and clinical data. Increasingly powerful informatics methods to detect subtle variations in image data are utilized in a wide variety of disciplines and models.
Data visualization is increasingly important for hypothesis generation, exploratory research and qualitative analysis. Emerging technologies that generate highly visual representations of data can foster recognition of novel associations.
Alignment of data structure with anticipated applications is important at all levels of bioinformatics and has major influence on the success of analysis and other applications.
Data Standardization & Integration
Integrating disparate data sources, whether for clinical or biological research, requires effective data standardization. Likewise, preparing data for translation from basic research settings into clinical applications requires understanding of the terminologies and standards used in each venue.
Systems analysis requires managing multiple scales and disparate data sources. Strategies for sharing data across non-affiliated systems and for analyzing biological data using biological pathways will be shared.