RENCI and iRODS will have a presence at the 19th Bio-IT World Conference and Expo, from October 6 – 8, 2020. Since its debut in 2002, the annual Bio-IT World Conference & Expo has established itself as a premier event showcasing the innovative IT and informatics applications and enabling technologies that are driving the future of precision medicine. The event highlights new frontiers in drug discovery & development, biomedical research, and clinical and healthcare initiatives made possible by cutting-edge technologies.
Below are talks from iRODS or RENCI, featuring our researchers, consortium members and iRODS users:
As commercial, governmental, and research organizations continue to move from manual pipelines to automated processing of their vast and growing datasets, they are struggling to find meaning in their repositories. With an open, policy-based platform, metadata can be elevated beyond assisting in just search and discoverability. Metadata can associate datasets, help build cohorts for analysis, coordinate data movement and scheduling, and drive the very policy that provides the data governance. Data management should be data centric, and metadata driven.
Michael Conway, Data Systems Architect/Engineer, National Institute of Environmental Health Sciences (NIEHS)
The topic of an NIH Data Commons has been an area of great interest and activity, as has the general FAIR data movement. These broad notions are playing out with a future focus while NIEHS works to build its own Data Commons to manage today’s research data. Managing daily work while observing future trends, incorporating key capabilities, often in a tentative and piecemeal fashion, without losing sight of the big picture; this is the challenge we all face.
Oleg Moiseyenko, Sr Cloud Architect, Scientific Computing Systems, Bristol-Myers Squibb
Next generation sequencing (NGS) is routinely being used in cancer research. This produces large amounts of data during data collection and as it gets processed through the pipeline. Tracking and apply context to large amount of data becomes a challenge. Using AWS as a mean of data delivery and processing, has the advantage of automating data delivery and processing. In additions, applying context to the data using iRODS can be automated as data gets delivered and processed. This will provide a primary source of metadata that can be used by other applications downstream.
Kimberly Robasky, PhD, Head, Translational Science, Renaissance Computing Institute (RENCI)
Researchers use biomarker and outcomes data to model and predict adverse events. However, access restrictions to safeguard patient privacy necessarily slow down the rate of discovery and increase research costs via IRB review. For these reasons, synthetic data that preserve patient-variable relationships have been an active area of research. We discuss current advances made by generative models in this area and the breakthrough AI technologies accelerating those advances.