Source: Interfolio F180

Andrew Su

Department of Integrative Structural and Computational Biology


Scripps Research Joint Appointments

Molecular Medicine
Skaggs Graduate School of Chemical and Biological Sciences

Research Focus

Our lab is interested biomedical discovery using quantitative methods. We apply the tools of computer science and statistics to a variety of projects spanning mouse genetics, transcriptional regulation, cancer biology, and immunology.

Our current research activities generally fall into three groups.

First, we build computational tools to enable and accelerate biomedical discovery. These online tools are typically targeted toward genetics and genomics researchers. Currently, we develop and maintain BioGPS and the Gene Wiki, both of which embrace the principle of 'community intelligence'. These tools harness the collective intelligence of the biological community to systematically improve the organization and access to gene annotation information.

Second, we directly engage in biomedical discovery through large-scale data mining. Most recently, we developed a method to utilize dense genotype maps in a diverse panel of inbred mice to do genome-wide association scans. We also extended this method to examine the genetic basis of gene expression variation, called expression QTL (or eQTL) analysis. We have used these approaches to identify, and in some cases validate, novel regulators of biological pathways and processes.

Third, we actively seek out new collaborations with experimental scientists to explore novel data sets and technology platforms. The rapid rate of biological data generation has only accelerated in recent years, and bioinformatics plays a critical role in the warehousing, analysis, and visualization of these data. We collaborate with many research groups both locally and globally, and focus on efficiently translating large data sets into testable hypotheses.


Ph.D. (Chemistry), The Scripps Research Institute, 2002
B.A. (Chemistry, Computing and Information Systems, Integrated Science), Northwestern University, 1998

Selected Publications

Good, B.; Su, A. Crowdsourcing for bioinformatics. Bioinformatics 2013, 29, 1925-1933.

Loguercio, S.; Good, B.; Su, A. Dizeez: an online game for human gene-disease annotation. PLoS One 2013, 8, e71171.

Clarke, E. L.; Loguercio, S.; Good, B.; Su, A. A task-based approach for Gene Ontology evaluation. J Biomedical Semantics 2013, 4 Suppl 1, S4.

Choi, N. M.; Loguercio, S.; Verma-Gaur, J.; Degner, S. C.; Torkamani, A.; Su, A.; Oltz, E. M.; Artyomov, M.; Feeney, A. J. Deep sequencing of the murine Igh repertoire reveals complex regulation of nonrandom V gene rearrangement frequencies. Journal of Immunology 2013, 191, 2393-2402.

Good, B.; Howe, D. G.; Lin, S. M.; Kibbe, W. A.; Su, A. Mining the Gene Wiki for functional genomic knowledge. BMC Genomics 2011, 12, 603.

Wu, C.; Orozco, C.; Boyer, J.; Leglise, M.; Goodale, J.; Batalov, S.; Hodge, C. L.; Haase, J.; Janes, J.; Huss, J. W.; Su, A. Biogps: An extensible and customizable portal for querying and organizing gene annotation resources. Genome Biology 2009, 10, R130.