Welcome to Avillach Lab at the Department of Biomedical Informatics
The real value in biomedical research lies not at the scale of any single source of data but in the ability to integrate and interrogate multiple, complementary datasets simultaneously.
The Avillach Lab, led by Paul Avillach, M.D., Ph.D., focuses on translational bioinformatics, specifically in integrating multiple heterogeneous sources of clinical and genomic data in a meaningful way. We are passionate about combining data across different scales and resolutions to enable new perspectives for essential biomedical questions. Our research focuses on developing novel methods and techniques for the integration of biological data, clinical cohorts, and Electronic Health Records to encompass biological observations.
We leverage the PIC-SURE (Patient-centered Information Commons: Standardized Unification of Research Elements) platform to manage a wide variety of arbitrarily large datasets with very little computing in a secured way by searching and extracting clinical and genomic variables of interest. Exposing the data not only at the file level but also at the variable and variant level directly accelerates creation of statistically ready dataframes. PIC-SURE has been deployed in a variety of environments, such as the NIH NHLBI BioData Catalyst Ecosystem, the Undiagnosed Disease Network, and Boston Children’s Hospital (see research).
Figure depicting various, interconnected “layers” of clinical and genomic data.
PIC-SURE contains both a graphical user interface (UI) and an application programming interface (API). With the UI, researchers can test their hypotheses by running multi-criteria queries at both the file and variable level and applying distinct clinical and genomic variable filters in the same search. With the API, users can filter and directly retrieve the data in an analysis-ready format using either R or python.