Faculty affiliated with the Center for Network and Storage-Enabled Collaborative Computational Science are addressing the challenges presented by collaborating on large, distributed or diverse data. Included in the Center is the NSF-funded OSiRIS project, a collaborative, multi-university venture led by MICDE faculty, and hosted by ARC-TS. Other research is ongoing in the following areas.
Research Areas
Biological and Behavioral Data Integration
This group develops new algorithms for integrating biological and behavioral data.
Biomedical Modeling
Center investigators conduct methodological research, healthcare applications and translate biomedical advanced to model, analyze and interpret data-driven observations spanning a broad range of challenges. Faculty also develop learning materials, organize training events, and facilitate trans-disciplinary collaborations. Biomedical modeling investigators test and validate innovative mathematical representations, computational algorithms and high-throughput processing workflows for interrogating complex datasets.
Data-driven Analysis of Genetic and Molecular Disease Mechanisms
This area of research centers on developing and applying statistical and computational approaches in understanding the cellular machinery by which genetic variants impacts expression phenotypes. This group is actively involved in the analysis working group of the NIH Genotype-Tissue Expression (GTEx) project. A primary goal is to efficiently integrate high-dimensional functional genomic and organismal-level phenotype data and uncover the genetic basis and molecular mechanism of complex diseases.
Simulated Oceanic Flow
This research group works on computer simulations of oceanic flows, e.g., currents, tides, and waves, on large supercomputers. We also compare the outputs of these complex ocean models with results from simple analytical models and with observations taken in-situ or remotely sensed from satellites.