ITTC Project


CAREER: Machine Learning Approaches for Genome-wide Biological Network Interference

Project Award Date: 02-22-2007



Description

Because of technological limitations, molecular biology research has had to focus on individual genes and gene products. This has led to a wealth of knowledge about individual cellular components and their functions. Isolated cellular components are not sufficient to understand most cellular functions, which are carried out by complex networks. It is therefore imperative to employ network-based approaches to address the complexity of living systems.

Scientists in life-science research must find how to computationally model and elucidate complex networks from high-throughput biological data sets. Thus, this research focuses on developing and applying novel computational methods for reconstructing genome-wide biological networks from high-throughput data.

ITTC researchers will develop and apply novel computational approaches for uncovering networks of interactions between genes and proteins. They will conduct related educational activities in a newly established bioinformatics program in the Department of Electrical Engineering and Computer Science at the University of Kansas. A wide-range of students, from high school through graduate school, will receive special training opportunities in the interdisciplinary area of bioinformatics.

ITTC Investigator Xue-wen Chen will develop machine learning methods for effectively integrating multiple prior knowledge from different data sources, highly heterogeneous data learning, and large-scale network learning. Learning with prior knowledge and highly heterogeneous data sources are fundamental to computational biology, information theory, machine learning, data mining, and other areas. The research will produce new methods and user-friendly software for molecular biologists.


Investigators

Faculty Investigator(s): Xue-wen Chen (PI)

Student Investigator(s): Mei Liu, Jong Jeong, Bing Han, Michael Wasikowski, Jae Kim, Alexander Senf, Matthew Mandelbaum, Patrick Dermyer, Richard Moorhead, Wenrong Zeng, Yuhao Yang, Jamie Bost, Yuxin Chen, George Li, Lauren Beesley, Tyler Graves


Project Sponsors


Primary Sponsor(s): NSF


Partner with ITTC

The Information and Telecommunication Technology Center at the University of Kansas has developed several assistance policies that enhance interactions between the Center and local, Kansas, or national companies. 

ITTC assistance includes initial free consulting (normally one to five hours). If additional support is needed, ITTC will offer one of the following approaches: 

Sponsored Research Agreement

Individuals and organizations can enter into agreements with KUCR/ITTC and provide funds for sponsored research to be performed at ITTC with the assistance of faculty, staff and students.

Licensing and Royalty/Equity Agreement

An ITTC goal is the development of investment-grade technologies for transfer to, and marketing by, local, Kansas, and national businesses. To enhance this process, the Center has developed flexible policies that allow for licensing, royalty, and equity arrangements to meet both the needs of ITTC and the company.

Commercialization Development

Companies with a technology need that can be satisfied with ITTC's resources can look to us for assistance. We can develop a relationship with interested partners that will provide for the development of a technology suited for commercialization.

ITTC Resource Access

ITTC resources, including computers and software systems, may be made available to Kansas companies in accordance with the Center's mission and applicable Regents and University policies.

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