Education

Ph.D., University of California, San Francisco, USA

Current position

Assistant Professor, Radiology at Massachusetts General Hospital Center for Systems Biology
Assistant Professor, Biological Chemistry & Molecular Pharmacology at Harvard Medical School
Harvard Medical School Associate Dean for Research Cores and Technology
Faculty Director, ICCB- Longwood Screening Facility

Dr. Shamu is a broadly trained cell biologist who has extensive experience and an international reputation in assay development and high-throughput screening technology. The ICCB-Longwood Screening Facility that she helped to establish and oversee supports both small molecule and RNAi screening, and has participated as a Screening Core in multiple NIH program/center grants, funded by NIAID, NCI, and the NIH Director’s Office.

In addition to her expertise in implementing new high throughput assay technologies, Dr. Shamu is active in the development of data standards and repositories for large-scale datasets from high-throughput assays. As co-investigator on the NIH-funded LINCS program, Dr. Shamu has played a leadership role in helping to develop metadata standards and public repositories for the emerging field of systems pharmacology. Her research focuses on data standards and repositories, and she is active in advocating for the use of public data repositories to document experimental reagents and protocols, and to share datasets. She serves as an editorial board member of Scientific Data.

Publications

1. Copeland, J. and Shamu, C. (2015). Informatics Considerations. In Haney, S. A. (eds), An Introduction to High Content Screening. John Wiley & Sons: Hoboken NJ. 
   
2. Vempati, U. D., Chung, C., Mader, C., Koleti, A., Datar, N., Vidovic, D., Wrobel, D., Erickson, S., Muhlich, J. L., Berriz, G., Benes, C. H., Subramanian, A., Pillai, A., Shamu, C. E. and Schurer, S. C. (2014). Metadata Standard and Data Exchange Specifications to Describe, Model, and Integrate Complex and Diverse High-Throughput Screening Data from the Library of Integrated Network-based Cellular Signatures (LINCS). J Biomol Screen. 19: 803-16.
   
3. Yilmazel, B., Hu, Y., Sigoillot, F., Smith, J. A., Shamu, C. E., Perrimon, N. and Mohr, S. E. (2014). Online GESS: prediction of miRNA-like off-target effects in large-scale RNAi screen data by seed region analysis. BMC Bioinformatics. 15: 192.
   
4. Tang, Y., Xie, T., Florian, S., Moerke, N., Shamu, C., Benes, C. and Mitchison, T. J. (2013). Differential determinants of cancer cell insensitivity to antimitotic drugs discriminated by a one-step cell imaging assay. J Biomol Screen. 18: 1062-71.
   
5. Rudnicki, S. P., Follen, J. V., Tolliday, N. J. and Shamu, C. E. (2012). Essentials for High Throughput Screening Operations. In Fu, H. (ed), Chemical Genomics. Cambridge University Press: New York NY. 
   
6. Shamu, C. E., Wiemann, S. and Boutros, M. (2012). On target: a public repository for large-scale RNAi experiments. Nat Cell Biol. 14: 115.
   
7. Tolopko, A. N., Sullivan, J. P., Erickson, S. D., Wrobel, D., Chiang, S. L., Rudnicki, K., Rudnicki, S., Nale, J., Selfors, L. M., Greenhouse, D., Muhlich, J. L. and Shamu, C. E. (2010). Screensaver: an open source lab information management system (LIMS) for high throughput screening facilities. BMC Bioinformatics. 11: 260.
   
8. Tsui, M., Xie, T., Orth, J. D., Carpenter, A. E., Rudnicki, S., Kim, S., Shamu, C. E. and Mitchison, T. J. (2009). An intermittent live cell imaging screen for siRNA enhancers and suppressors of a kinesin-5 inhibitor. PLoS One. 4: e7339.
   
9. Birmingham, A., Selfors, L. M., Forster, T., Wrobel, D., Kennedy, C. J., Shanks, E., Santoyo-Lopez, J., Dunican, D. J., Long, A., Kelleher, D., Smith, Q., Beijersbergen, R. L., Ghazal, P. and Shamu, C. E. (2009). Statistical methods for analysis of high-throughput RNA interference screens. Nat Methods. 6: 569-75.
10. Inglese, J., Shamu, C. E. and Guy, R. K. (2007). Reporting data from high-throughput screening of small-molecule libraries. Nat Chem Biol. 3: 438-41.
11. Shamu, C. E., Flierman, D., Ploegh, H. L., Rapoport, T. A. and Chau, V. (2001). Polyubiquitination is required for US11-dependent movement of MHC class I heavy chain from endoplasmic reticulum into cytosol. Mol Biol Cell. 12: 2546-55.
12. Shamu, C. E., Story, C. M., Rapoport, T. A. and Ploegh, H. L. (1999). The pathway of US11-dependent degradation of MHC class I heavy chains involves a ubiquitin-conjugated intermediate. J Cell Biol. 147: 45-58.
13. Raymond, C. S., Shamu, C. E., Shen, M. M., Seifert, K. J., Hirsch, B., Hodgkin, J. and Zarkower, D. (1998). Evidence for evolutionary conservation of sex-determining genes. Nature. 391: 691-5.
14. Shamu, C. E. and Walter, P. (1996). Oligomerization and phosphorylation of the Ire1p kinase during intracellular signaling from the endoplasmic reticulum to the nucleus. EMBO J. 15: 3028-39.
15. Cox, J. S., Shamu, C. E. and Walter, P. (1993). Transcriptional induction of genes encoding endoplasmic reticulum resident proteins requires a transmembrane protein kinase. Cell. 73: 1197-206.
16. Shamu, C. E. and Murray, A. W. (1992). Sister chromatid separation in frog egg extracts requires DNA topoisomerase II activity during anaphase. J Cell Biol. 117: 921-34.
    
17. Miller, D. M., Shen, M. M., Shamu, C. E., Burglin, T. R., Ruvkun, G., Dubois, M. L., Ghee, M. and Wilson, L. (1992). C. elegans unc-4 gene encodes a homeodomain protein that determines the pattern of synaptic input to specific motor neurons. Nature. 355: 841-5.

Complete list of published works. For a complete list of 32 papers and chapters published, see
http://www.ncbi.nlm.nih.gov/sites/myncbi/1VqruTpIulqkq/bibliography/47596070/public