New protein sequences offer unprecedented opportunities for knowledge-based sequence annotations. By aiming to automatically transfer experimentally gained biological knowledge from model organisms to newly sequenced genomes, researchers will expedite biological discovery.

Investigators are refining software that aids in proteomic and other life sciences research.

ITTC investigators are procuring a powerful web application server to replace the server that currently runs Web Server Tracker.

This research focuses on developing and applying novel computational methods for reconstructing genome-wide biological networks from high-throughput data.

Researchers will develop an online repository for the sharing, distribution, and evaluation of small-scale, public-domain bioinformatics software tools.

The project aims to better understand inter- and intra- molecular long-range interactions, to apply gained knowledge towards finding solutions for neurodegenerative diseases, and to improve prediction of protein 3-D structure.

With the steady increase in genomic data, the impact to centers using the public domain Genomic Unified Schema, GUS could be significant. ITTC will provide essential functionality for genome-analysis research and development.

University of Kansas researchers are developing a suite of data conversion and compression routines capable of generating compact repositories of mass spectrometry data in a unified format suitable for efficient analysis and rapid reconstitution to vendor-specific form.

Development of a systematic integrated bioinformatics information infrastructure is critical for fostering such multi-faceted (and often inter-related) bioresearch efforts. ITTC research will devise and implement new-networked bioinformatics infrastructure resources for facilitating collaborative, cross-disciplinary biological studies of relevance to chemical and biological defense.

A computing facility will facilitate the development, testing and deployment of new computing technologies in support of research on a variety of life sciences problems. The close collaboration between chemists, biologists, mathematicians, and computer scientists using this facility will result in the creation of new computing and information technologies and will directly lead to increasing our understanding of biological systems.

The long-term objectives of this research include better understanding protein functions based on their domain structures and predicting protein domains in terms of their functions.

It is the goal of this project to develop new computational models for inferring gene networks from microarray data, help investigators understand the molecular mechanisms of epilepsy, and provide new targets for therapeutic intervention in seizure development.