• Ph.D. (2016) Computational Biology, Univ. of Kansas
• B.A. (2009) Mathematics, Goshen College
• Employment:
  • 2016-present Postdoctoral Research Associate, LANL
  • 2015 (summer) Software Engineer Intern, Orion Health
  • 2011-2016 Graduate Research Assistant, Univ. of Kansas
  • 2010-2011 Graduate Teaching Assistant, Univ. of Kansas

Research Interests:

• Dynamics of signal transduction in immune cells
• Cellular interpretation of environmental information
• Developing novel tools and methods for systems biology modeling

Selected Recent Publications:

Google Scholar profile
1. Suderman, R., Hlavacek, W.S. Modeling cell activation at ultra-low ligand concentrations, Technical Report (LA-UR-18-22083) doi: 10.2172/1425782
2. Suderman, R., Mitra, E.D., Lin, Y.T., Feng, S., Erickson, K.E., Hlavacek, W.S. Generalizing Gillespie's Direct Method to Enable Network-Free Simulations, Bull Math Biol doi: 10.1007/s11538-018-0418-2
3. Suderman, R. Schauer, A. Deeds, E.J. Understanding the dynamics of scaffold-mediated signaling, bioRxiv 167205; doi: 10.1101/167205
4. Suderman, R., Hlavacek, W.S. TRuML: A Translator for Rule-Based Modeling Languages, Proceedings of the 8th ACM International Conference on Bioinformatics, Computational Biology,and Health Informatics (ACM-BCB '17) 372-377, doi: 10.1145/3107411.3107471
5. Suderman, R., Bachman, J.A., Smith, A., Sorger, P.K., Deeds, E.J. Fundamental trade-offs between information flow in single cells and cellular populations, Proc Natl Acad Sci USA, 114 (22) 5755-5760, doi: 10.1073/pnas.1615660114 (2017)
6. Suderman, R., Deeds, E.J. Machines vs. Ensembles: Effective MAPK Signaling through Heterogeneous Sets of Protein Complexes, PLoS Computational Biology, 9 (10) e1003278 (2013)