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This article is part of the supplement: Nineteenth Annual Computational Neuroscience Meeting: CNS*2010

Open Access Poster Presentation

Building an institutional base for Computational Neuroscience: the CBI at UTSA/UTHSCSA

Zhiwei Wang1, Kay Robbins2, Yufeng Wang3, Carolina Livi5, Alan D Coop4, Fidel Santamaria3, Carola Wenk2 and James M Bower4*

Author Affiliations

1 Computational Biology Initiative, UTSA, USA

2 Department of Computer Science, UTSA, USA

3 Department of Biology, UTSA, USA

4 Research Imaging Institute, University of Texas Health Sciences Center at San Antonio, San Antonio, TX 78229, USA

5 Department of Nuclear Medicine, University of Texas Health Sciences Center at San Antonio, San Antonio, TX 78229, USA

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BMC Neuroscience 2010, 11(Suppl 1):P67  doi:10.1186/1471-2202-11-S1-P67

The electronic version of this article is the complete one and can be found online at: http://www.biomedcentral.com/1471-2202/11/S1/P67


Published:20 July 2010

© 2010 Bower et al; licensee BioMed Central Ltd.

Poster Presentation

In the Spring of 2005, The University of Texas, San Antonio established the Computational Biology Initiative (CBI) as a mechanism to introduce and then support the local use of computational tools for research and education. In 2006, the CBI expanded to include researchers and educators at the University of Texas Health Science Center, San Antonio. Built on a novel mechanism of computational liaisons, and with a significant focus on education and user support, the CBI has grown to include over 300 registered users, serving 71 individual research laboratories and multiple undergraduate and graduate courses.

Methods

The CBI core facility at UTSA is built around a High Performance Computing System, a high throughput and high availability data storage system, and a number of high-end workstations. The CBI also supports a number of computational software packages including MatLab, Mathematica, Imaris, Genespring, GENESIS, etc. The CBI is also fully integrated with other core facilities including a Research Imaging Core and a Proteonimics core. In addition to providing resources, however, the CBI from the outset has focused on educating undergraduates, graduate students, postdoctoral fellows and faculty in the use of computational techniques. In that capacity the CBI has sponsored 17 training workshops with more than 400 participants to date. A novel initial feature of the CBI involved the hiring of computational liaisons to serve as the interface with individual laboratories and research projects. These liaisons were Ph.D. research biologists who had also been trained in computation. As trained biologists, they understand the nature of biological experimentation, while their computational training allowed them to infuse computational approaches into existing research projects.

Results

At present, the CBI has over 300 individual registered users. The CBI currently supports grants totaling $23,800,000. Reflecting the extent to which the CBI has now become a core component of research, the CBI director position was recently approved as a State Funding Line. The CBI was also recently awarded the HUB Advocate Department Award for 2009.

Conclusions

The CBI represents a novel, but successful approach to establishing and then supporting the increased use of computational techniques in biological research broadly defined within a university setting.

Acknowledgements

Research supported by RCMI ($1.6 M) and the UT System ($2.5M)