XSEDE Proposal for Jetstream Resources
XSEDE Educational Allocation Resource Justification
Title: Teaching Bioinformatics to Biologists at UC San Diego
PI: Dr. Barry J Grant (
[email protected])
University of California, San Diego
9/21/2017
Overview:
XSEDE Jetstream resources are requested to support the teaching of a new
bioinformatics graduate course for biologists at UC San Diego. This course,
BGGN-213 ("Foundations of Bioinformatics") provides a hands-on introduction to the
computer-based analysis of genomic and biomolecular data. Major topics include:
Genome informatics, Structural informatics, Transcriptomics, UNIX for bioinformatics,
and Bioinformatics data analysis with R. Full course details are available at: < https://
bioboot.github.io/bggn213_f17/ >
Critical Need:
Modern biomedical research is generating ever increasing quantities of complex
biological data. As the rate of this data generation continues to outpace the rate at
which biologists are able to analyze these data, there is a critical need for new
bioinformatics training to help the next generation of biologists drive the collection and
analysis of this “big data revolution” in the biosciences.
Why XSEDE?
The Division of Biological Sciences at UC San Diego has no suitable UNIX compute
server to use for this course. Limiting students to their own laptops or departmental
desktop windows machines will severely limit the scope and utility of this course.
Access to XSEDE Jetstream resources will enable students to learn and gain
proficiency in modern bioinformatics workflows and best practices for reproducible
research on todays large genomic and biomolecular datasets.
Resources Requested:
Between 24 and 30 students will require an estimated maximum of 17,800 Service
Units. Students will use these resources from week 5 of the course onward (10/12/17
to 12/12/17).
A maximum of 32 Virtual Machines and associated public IP addresses (for SSH
access) will be required along with 2TB of storage space total (students will download
and store several eukaryotic genomes along with several small molecule and protein
structure datasets).
BIOGRAPHICAL SKETCH: BARRY J. GRANT
A. Professional Preparation
• Queen’s University of Belfast, UK Biochemistry B.Sc. (1999)
• University of York, UK Bioinformatics M.Res. (2000)
• University of York, UK Chemistry Ph.D. (2005)
• University of California, San Diego Biophysics Postdoc (2005-2009)
B. Appointments
• Assistant Professor Division of Biological Sciences (2017-present)
University of California, San Diego, CA.
• Assistant Professor Department of Computational Medicine & Bioinformatics (2011-2017)
University of Michigan, Ann Arbor, MI.
• Bioinformatics Specialist (Senior Scientist) Howard Hughes Medical Institute (2009-2011)
University of California, San Diego, CA.
• Bioinformatics Scientist deCODE Genetics Inc., Reykjavik, Iceland. (2000)
C. Publications
Note. Complete bibliography and full-text options available from: http://thegrantlab.org/publications/
Publications closely related to project
• Yao XQ, Skjaerven L, Grant BJ. Rapid characterization of allosteric networks with ensemble normal
mode analysis. J Phys Chem B. 2016. DOI: 10.1021/acs.jpcb.6b019912016.
• Yao XQ, Malik RU, Griggs NW, Skjaerven L, Traynor JR, Sivaramakrishnan S, Grant BJ. Dynamic
coupling and allosteric networks in the alpha subunit of heterotrimeric G proteins. J Biol Chem.
2016;291(9):4742-53. PMCID: 4813496.
• Scarabelli G, Soppina V, Yao XQ, Atherton J, Moores CA, Verhey KJ, Grant BJ. Mapping the
processivity determinants of the kinesin-3 motor domain. Biophys J. 2015;109(8):1537-40. PMCID:
4624112.
• Scarabelli G, Grant BJ. Mapping the structural and dynamical features of kinesin motor domains.
PLoS Comput Biol. 2013;9(11):e1003329. PMCID: 3820509.
• Grant BJ, Gheorghe DM, Zheng W, Alonso M, Huber G, Dlugosz M, McCammon JA, Cross RA.
Electrostatically biased binding of kinesin to microtubules. PLoS Biol. 2011;9(11):e1001207. PMCID:
3226556.
Other significant publications
• Skjaerven L, Jariwala S, Yao XQ, Grant BJ. Online interactive analysis of protein structure
ensembles with Bio3D-web. Bioinformatics. 2016; (in press).
• Skjaerven L, Yao XQ, Scarabelli G, Grant BJ. Integrating protein structural dynamics and
evolutionary analysis with Bio3D. BMC Bioinformatics. 2014;15:399. PMCID: 4279791.
• Scarabelli G, Grant BJ. Kinesin-5 allosteric inhibitors uncouple the dynamics of nucleotide,
microtubule, and neck-linker binding sites. Biophys J. 2014;107(9):2204-13. PMCID: 4223232.
• Yao XQ, Grant BJ. Domain-opening and dynamic coupling in the alpha-subunit of heterotrimeric G
proteins. Biophys J. 2013;105(2):L08-10. PMCID: 3714883.
• Grant BJ, Rodrigues AP, ElSawy KM, McCammon JA, Caves LS. Bio3D: An R package for the
comparative analysis of protein structures. Bioinformatics. 2006;22(21):2695-6.
D. Selected Synergistic Activities
• Excellence in Basic Science Teaching Award, Computational Medicine and Bioinformatics,
University of Michigan (2013).
Awarded 17,800 SUs (equivalent to $3,007)