Our History

The Computational Biology and Bioinformatics Group of the Biosciences Division was created in February 1997. The Computational Biology Program continues the ORNL biomedical research that started 50 years ago. Building on strong and often unique competencies and special facilities in bioinformatics, the section pursues research and development to understand the fundamental questions in the life sciences, biological systems, and human health.

Our Mission

Our mission is to address fundamental questions in the life sciences and provide information and analytical resources to the wider biology research community. We achieve these goals through our research and development at the intersection of the life sciences, mathematics, information technology, and computational science. Our research program covers several high-impact scientific areas including:

• methods for gene discovery and the analysis of genomes,
• simulation and modeling of protein folding and functional and structural classification using artificial intelligence-based techniques,
• systems for computational forensics and video processing,
• medical applications of intelligent systems, and
• the development of bioinformatics tools and systems for use by the research community

Our Challenge

The interpretation of sequenced genomes represents our next great challenge. Interfacing computing and biology, we hope to provide knowledge which is of immeasurable value to medical research, biotechnology, the pharmaceutical industry and researchers in a host of fields ranging from microorganism metabolism, to structural biology, to bioremediation. We are developing new ways of recognizing and understanding the many important features of genomes. We are defining the infrastructure necessary for high quality and comprehensive analysis and sequence annotation processes.

We are constructing a comprehensive framework for analysis and annotation using a distributed interoperable system of analysis servers and biodatabases. We have designed and continue to develop major online analytical systems for genomics such as the GRAIL® and genQuest Internet servers.

The generation of new genome sequence and functional data is also one of our focus areas, and we are developing high-throughput sequencing capabilities and advanced sequencing automation. In order to deal with the flood of genome data, we have set a high priority to improve the efficiency of protein characterization based on protein sequence. We are developing new algorithms and tools for protein structure prediction and functional classification using a variety of techniques such as neural networks, protein threading, global optimization, genetic algorithms, and molecular dynamics.

With the increased amount and complexity of biodata, an we place an emphasis is the architectural design and construction of integrated analysis systems, databases, and knowledge bases for such data. We are addressing fundamental research issues related to the design, development and maintenance of bioinformation databases, Internet tools, query systems, and other types of bioresources. Our research issues include biodata representation, database and analysis system interoperation, data integration, automated agent-based data retrieval and update technologies, semantics, data mining, and knowledge discovery methods.