Computational Biology Values
We are a collection of labs who use computational methods to learn about biology. We want computational biology to be a welcoming and inclusive place for people of all backgrounds,
- advancing biology via rigorous and reproducible research
- forming a nexus of labs leading to collaborative science
- placing an emphasis on mentorship of the next generation of researchers
- fostering a diverse community of computational biologists
The Herbold Computational Biology Program was established in 2007 with the support of Bob and Pat Herbold. We merge traditional biological sciences with advanced training in physics, statistics, mathematics and computer science. By using computational methods and tools to address biological questions, we explore what was once purely experimental or purely computational/statistical, allowing our program to address new areas of research.
The Computational Biology Program (CB) strives to provide a respectful environment for everyone here, irrespective of race, color, religion, sex (including pregnancy, childbirth, and related medical conditions), gender, sexual orientation, gender identity or expression, national origin, ancestry, ethnicity, age, physical or mental disability, citizenship, marital status, genetic information, genetic status or characteristics, military or veteran status, or on any basis protected by an applicable law (a “protected characteristic”).
Faculty and Labs
Our faculty members have expertise in transcription/translation control, adaptive-immune system dynamics, and phylogenetics.
News
See the latest news about our program scientists, research, grants and discoveries.
The Mahan Postdoctoral Fellowship
The Mahan postdoctoral fellowship supports exceptional young scientists in the early stages of their careers. We offer fellows a 21-month stipend as they pursue their proposed research project, alongside a mentor in one of our Herbold Computational Biologist laboratories.
Recent Publications:
- Loes, A. N., Tarabi, R. a. L., Huddleston, J., Touyon, L., Wong, S. S., Cheng, S. M. S., Leung, N. H. L., Hannon, W. W., Bedford, T., Cobey, S., Cowling, B. J., & Bloom, J. D. (2024). High-throughput sequencing-based neutralization assay reveals how repeated vaccinations impact titers to recent human H1N1 influenza strains. Journal of Virology, 98(10). https://doi.org/10.1128/jvi.00689-24
- Dadonaite, B., Ahn, J. J., Ort, J. T., Yu, J., Furey, C., Dosey, A., Hannon, W. W., Baker, A. L. V., Webby, R. J., King, N. P., Liu, Y., Hensley, S. E., Peacock, T. P., Moncla, L. H., & Bloom, J. D. (2024). Deep mutational scanning of H5 hemagglutinin to inform influenza virus surveillance. PLoS Biology, 22(11), e3002916. https://doi.org/10.1371/journal.pbio.3002916
- Boyle, G. E., Sitko, K., Galloway, J. G., Haddox, H. K., Bianchi, A. H., Dixon, A., Wheelock, M. K., Vandi, A. J., Wang, Z. R., Thomson, R. E. S., Garge, R. K., Rettie, A. E., Rubin, A. F., Geck, R. C., Gillam, E. M. J., DeWitt, W. S., Matsen, F. A., & Fowler, D. M. (2024). Deep mutational scanning of CYP2C19 in human cells reveals a substrate specificity-abundance tradeoff. Genetics. https://doi.org/10.1093/genetics/iyae156
- Gabel, A. M., Belleville, A. E., Thomas, J. D., Pineda, J. M. B., & Bradley, R. K. (2024). APC mutations dysregulate alternative polyadenylation in cancer. Genome Biology, 25(1). https://doi.org/10.1186/s13059-024-03406-4
- Weissman, J. L., Chappell, C. R., De Oliveira, B. F. R., Evans, N., Fagre, A. C., Forsythe, D., Frese, S. A., Gregor, R., Ishaq, S. L., Johnston, J., R, B. K., Matsuda, S. B., McCarren, S., De La Campa, M. O. A., Roepke, T. A., Sinnott-Armstrong, N., Stobie, C. S., Talluto, L., & Vargas-Muñiz, J. M. (2024). Queer- and trans-inclusive faculty hiring—A call for change. PLoS Biology, 22(11), e3002919. https://doi.org/10.1371/journal.pbio.3002919
- Sinnott-Armstrong, N., Fields, S., Roth, F., Starita, L. M., Trapnell, C., Villen, J., Fowler, D. M., & Queitsch, C. (2024). Understanding genetic variants in context. eLife, 13. https://doi.org/10.7554/elife.88231
Groups
Computational biology consists of members spanning Public Health Science, Basic, Human Biology, VIDD, and a variety of departments at the University of Washington.
We welcome both computational researchers who want to learn about biology, as well as biologists who want to learn computational methods. The Fred Hutch is well equipped to bring people in the latter category up to speed. Comp bio faculty run MCB 536, a course to introduce computational tools to biology graduate students, and our scientific computing documentation is comprehensive and up to date.
phyloseminar.org
Access a free monthly seminar series on phylogenetics, organized by Dr. Frederick “Erick” Matsen. Attend seminars online in real time or via recordings at your convenience.
Mailing Address
Fred Hutchinson Cancer Center
Herbold Computational Biology Program
1100 Fairview Avenue North (Mailstop: S2-140)
Seattle, Washington 98109
Program Contacts
Administrative Coordinator - Carlyn Fausto, cfausto@fredhutch.org
Research Administrator - Eleanor Vail, evail@fredhutch.org
Research Administrator - Samantha Smallwood, sdistel@fredhutch.org
Research Administrator - Ruby Mae San Pedro, rsanpedr@fredhutch.org
Research Administrator Manager - An Tyrrell, atyrrell@fredhutch.org
Program Operations Director - Melissa Alvendia, malvendi@fredhutch.org
Contact Carlyn Fausto (cfausto@fredhutch.org) to gain access to Comp Bio's internal website.