Research
The purpose of the Center is to construct KnowEnG, an E-science framework for genomics where biomedical scientists will have access to powerful methods of data mining, network mining, and machine learning to extract knowledge out of existing genomics data. They will use KnowEnG to analyze their own data sets in the context of a massive knowledge-base of community data sets called the Knowledge Network that will be at the heart of the system.
Knowledge Network
Knowledge Network research works to develop a pipeline which can produce a heterogeneous network, termed the “Knowledge Network,” which functions as a compendium of community data sets which is ready for computation and investigation.
Project Leaders
Saurabh Sinha
Analytics
Data science researchers are identifying the analytical functions at the core of a wide array of bioinformatics algorithms. They will define and build efficient approaches to these core functions.
Project Leaders
Saurabh Sinha
Jiawei Han
Discovery
A substantial portion of the Center’s activity is devoted to discovery projects aimed at testing and demonstrating the utility of KnowEnG for transforming big data to knowledge. These projects span a broad range of biological enquiry:
Project Leaders
Richard Weinshilboum
Saurabh Sinha
Lisa Stubbs
Gene Robinson
William Metcalf
Liewei Wang
Cyberinfrastructure
Systems engineering specialists are building a highly scalable Cloud-based framework where the analytical functions can be accessed by each user in parallel. The framework will be made available through a web portal linked to a commercial Cloud and will also be installable on local Cloud infrastructures of the user’s organization.
Project Leaders
Saurabh Sinha
Umberto Ravaioli
Roy Campbell
Visualization
Specialists in user interface design, visualization, literature mining and information retrieval are developing the front end to KnowEnG, with innovative capabilities such as automated analysis recommendation, Feature Exploration using dimensions from the Knowledge Network Database, and visualization and interaction methods developed to address issues specific to these types of data.
Project Leaders
Colleen Bushell