Key Words: Structural Genomics; Metagenomics; Bioinformatics and Computational Inference

My research now largely focuses on structural genomics (SG) and metagenomics (MG), along with various bioinformatics and computational methods for probing SG and MG data and for community engagement via web services technology. 
Structural genomics is the high throughput (HT) determination of protein structures, choosing protein targets that are unlike any protein of known structure and of previously known function.  Our Joint Center for Structural Genomics (JCSG: http://www.jcsg.org), funded by the NIH NIGMS Protein Structure Initiative, created a HT pipeline to deliver the structures of novel proteins and enable us to explore the protein universe through the tools of bioinformatics.   Since then, we have been able to characterize the entire soluble proteome of a deeply-rooted, eubacterial thermophile, Thermotaga maritime, by a combination of computationally predicted structures were mesophilic homologues exist and by HT structure determination otherwise. We also use our three dimensional atomic-level structures to inform metabolic models, genome annotations, and other studies in functional biology, including an understanding of the central machinery of life.  
Metagenomics is the sequencing or functional study of uncloned (and typically unculturable) microbial communities (“meta” genome population) through direct analysis of environmental or host-constrained samples.  We have established a community web based metagenomics and microbial sequence data (and associated details or metadata) resource for the computational study of MG populations with a focus on the ecology of such complex populations.  This resource, funded by the Gordon and Betty Moore Foundation, is termed CAMERA (http://camera.calit2.net ) or Community Cyberinfrastructure for Advanced Marine Microbial Ecological Research and Analysis, which employs a Kepler Workflow to include a range of options for users and permit ready incorporation of new third party software tools.  
The SG and MG research areas are connected.  In particular, our SG research empowers IT-based efforts to help characterize the nature of bacterial communities, by advancing annotation (sequence information) and other functional information on mechanism.   We have also used web-server based technology that is scalable and extensib­le to build a pilot for a enhancing the impact of the proteins we and others determine through SG efforts, which can serve for generally as a communication and collaboration platform for many areas of biology, including metagenomics.  As an experiment in advancing functional understanding of the novel proteins characterized in HT pipelines, the first instantiation of such pilots is TOPSAN (http://www.topsan.org), The Open Protein Annotation Network.
I also facilitate larger scale interdisciplinary research development and initiatives, as well as comparable educational opportunities built upon extant research strengths. A major challenge of deep relevance to the pharmacology department of especial interest would be to establish a major collaborative approach to understanding the mechanisms for molecular recognition, a challenge that would require participation and have an impact across many areas of our campus, including SSPPS, SOM (notably, including pharmacology), SIO, JSOE, and the physical and biological sciences (notably, including the chemistry-biochemistry department).
Most relevant to my research and campus vision are review papers I have edited on a broad range of opportunities for computational science to contribute to experimental biology; some are shown below, as are some of our structural genomics and metagenomics contributions, and also the application of cyberinfrastructure to benefit biological and biomedical science. 

Recent Publications

Chung, S. and Wooley, J. (1997), "The Likely Impact of Developments in Computer-based information, Networking and Research: A Perspective from the Biological Sciences," in Equipping Science for the 21st Century, ed. John Irvine, Ben Martin, Dorothy Griffiths and Roel Gathier, Edward Elgar Press, Cheltenham, United Kingdom.

Wooley, J. (1999), "Trends in Computational Biology" Journal of Computational Biology 6, 459-474.
Head-Gordon, T. and Wooley, J.C. (2001) "Computational Challenges in Structural and Functional Genomics” IBM Systems Journal 40 265-296

Fraser, C. and Wooley, J. (2002) Microbial Genomics, NSF Arlington, VA

Wooley, J. (2004) Building a Cyberinfrastructure for the Biological Sciences (CIBIO), NSF, Arlington, VA

Wooley, J. (2004) Exploring an emerging frontier: the interface between biology and computing” in Converging Science, Microsoft Press, Cambridge, UK. 

Wooley, J. and Lin, H. (2005) Catalyzing Inquiry at the Interface of Computing and Biology, National Academy of Science Press, Washington, D.C.

Arima, Kayo and John Wooley. “Chapter 14: Metagenomics.” Computational Methods for Understanding Bacterial and Archaeal Genomes. Ed. Ying Xu and M. Peter Gogarten. London: Imperial College Press, 2008. 345-96.