Scott C. Schmidler | Scholars@Duke

Scott C. Schmidler
Associate Professor of Statistical Science

Current Appointments & Affiliations

Associate Professor of Statistical Science, Statistical Science, Trinity College of Arts & Sciences 2010
Associate Professor of Computer Science, Computer Science, Trinity College of Arts & Sciences 2011

Contact Information

223D Old Chem, Durham, NC 27708-0251
Box 90251, Isds, Durham, NC 27708-0251
scott.schmidler@duke.edu (919) 684-8064
http://www.stat.duke.edu/~scs/

Background
Education, Training, & Certifications
- Ph.D., Stanford University 2002
- B.A., University of California at Berkeley 1995
Duke Appointment History
- Assistant Professor in the Institute of Statistics and Decision Sciences, Statistical Science, Trinity College of Arts & Sciences 2006 - 2010
- Assistant Professor in the Institute of Statistics and Decision Sciences, Statistical Science, Trinity College of Arts & Sciences 2002 - 2006
- Lecturer, University, Statistical Science, Trinity College of Arts & Sciences 2000 - 2002
Research
Selected Grants
- Deep Topological Sampling of Protein Structures - non-competing renewal for Year 3 awarded by National Institutes of Health 2017 - 2021
- Bioinformatics and Computational Biology Training Program awarded by National Institutes of Health 2005 - 2020
- EMSW21-RTG: Geometric, Topological awarded by National Science Foundation 2011 - 2018
- Advances in Scalable Monte Carlo Algorithms for Bayesian Statistics awarded by National Science Foundation 2014 - 2017
- Structural Biology and Biophysics Training Program awarded by National Institutes of Health 1994 - 2015
- Mechanistic Studies of Complex Protein Folding Reactions awarded by National Institutes of Health 2008 - 2013
- Bayesian Analysis of Shapes and Curves with Applications in Bioinformatics awarded by National Science Foundation 2006 - 2007
- Statistical Models of Biopolymer Sequence and Folding awarded by National Science Foundation 2002 - 2005
Publications & Artistic Works
Selected Publications
- Academic Articles
  - Darnell, Cynthia L., Peter D. Tonner, Jordan G. Gulli, Scott C. Schmidler, and Amy K. Schmid. “Systematic Discovery of Archaeal Transcription Factor Functions in Regulatory Networks through Quantitative Phenotyping Analysis..” Msystems 2, no. 5 (September 19, 2017). https://doi.org/10.1128/mSystems.00032-17.
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  - VanDerwerken, D., and S. C. Schmidler. “Monitoring Joint Convergence of MCMC Samplers.” Journal of Computational and Graphical Statistics 26, no. 3 (July 3, 2017): 558–68. https://doi.org/10.1080/10618600.2017.1297240.
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  - Cooke, B., D. P. Herzog, J. C. Mattingly, S. A. Mckinle, and S. C. Schmidler. “Geometric ergodicity of two-dimensional hamiltonian systems with a Lennard-Jones-like repulsive potential.” Communications in Mathematical Sciences 15, no. 7 (January 1, 2017): 1987–2025. https://doi.org/10.4310/CMS.2017.v15.n7.a10.
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  - Ben-Shachar, Rotem, Scott Schmidler, and Katia Koelle. “Drivers of Inter-individual Variation in Dengue Viral Load Dynamics..” Plos Computational Biology 12, no. 11 (November 17, 2016). https://doi.org/10.1371/journal.pcbi.1005194.
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  - Estrada, Rolando, Carlo Tomasi, Scott C. Schmidler, and Sina Farsiu. “Tree Topology Estimation..” Ieee Transactions on Pattern Analysis and Machine Intelligence 37, no. 8 (August 2015): 1688–1701. https://doi.org/10.1109/TPAMI.2014.2382116.
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  - Herman, Joseph L., Christopher J. Challis, Ádám Novák, Jotun Hein, and Scott C. Schmidler. “Simultaneous Bayesian estimation of alignment and phylogeny under a joint model of protein sequence and structure..” Molecular Biology and Evolution 31, no. 9 (September 2014): 2251–66. https://doi.org/10.1093/molbev/msu184.
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  - Daniels, Kyle G., Nam K. Tonthat, David R. McClure, Yu-Chu Chang, Xin Liu, Maria A. Schumacher, Carol A. Fierke, Scott C. Schmidler, and Terrence G. Oas. “Ligand concentration regulates the pathways of coupled protein folding and binding..” J Am Chem Soc 136, no. 3 (January 22, 2014): 822–25. https://doi.org/10.1021/ja4086726.
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  - Rodriguez, Abel, and Scott C. Schmidler. “BAYESIAN PROTEIN STRUCTURE ALIGNMENT..” The Annals of Applied Statistics 8, no. 4 (January 2014): 2068–95. https://doi.org/10.1214/14-AOAS780.
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  - Wang, R., and S. C. Schmidler. “Bayesian multiple protein structure alignment.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 8394 LNBI (January 1, 2014): 326–39. https://doi.org/10.1007/978-3-319-05269-4-27.
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  - Ji, C., and S. C. Schmidler. “Adaptive Markov chain Monte Carlo for Bayesian variable selection.” Journal of Computational and Graphical Statistics 22, no. 3 (December 17, 2013): 708–28. https://doi.org/10.1080/10618600.2013.819178.
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  - Challis, Christopher J., and Scott C. Schmidler. “A stochastic evolutionary model for protein structure alignment and phylogeny..” Molecular Biology and Evolution 29, no. 11 (November 2012): 3575–87. https://doi.org/10.1093/molbev/mss167.
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  - Wolpert, R. L., and S. C. Schmidler. “α-Stable limit laws for harmonic mean estimators of marginal likelihoods.” Statistica Sinica 22, no. 3 (July 1, 2012): 1233–51. https://doi.org/10.5705/ss.2010.221.
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  - Zheng, N., S. C. Schmidler, D. Marks, and D. Brady. “Computer experiment and global optimization of layered monocentric lens systems.” Optik 123, no. 14 (July 1, 2012): 1249–59. https://doi.org/10.1016/j.ijleo.2011.07.058.
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  - Wilson, Melanie A., Edwin S. Iversen, Merlise A. Clyde, Scott C. Schmidler, and Joellen M. Schildkraut. “BAYESIAN MODEL SEARCH AND MULTILEVEL INFERENCE FOR SNP ASSOCIATION STUDIES..” Ann Appl Stat 4, no. 3 (September 1, 2010): 1342–64. https://doi.org/10.1214/09-aoas322.
    Full Text Open Access Copy Link to Item
  - Jia, B., J. Li, S. Huang, S. C. Schmidler, and Y. K. Wu. “Electron beam energy spread measurements using optical klystron radiation.” Physical Review Special Topics Accelerators and Beams 13, no. 8 (August 4, 2010). https://doi.org/10.1103/PhysRevSTAB.13.080702.
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  - Wiehe, K., T. B. Kepler, and S. C. Schmidler. “P19-50. Simulation of an MPER peptide samples epitope conformations of two broadly neutralizing antibodies.” Retrovirology 6, no. SUPPL. 3 (October 22, 2009). https://doi.org/10.1186/1742-4690-6-S3-P370.
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  - Woodard, D. B., S. C. Schmidler, and M. Huber. “Conditions for rapid mixing of parallel and simulated tempering on multimodal distributions.” Annals of Applied Probability 19, no. 2 (April 1, 2009): 617–40. https://doi.org/10.1214/08-AAP555.
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  - Woodard, D. B., S. C. Schmidler, and M. Huber. “Sufficient conditions for torpid mixing of parallel and simulated tempering.” Electronic Journal of Probability 14 (January 1, 2009): 780–804. https://doi.org/10.1214/EJP.v14-638.
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  - Cooke, Ben, and Scott C. Schmidler. “Statistical prediction and molecular dynamics simulation..” Biophysical Journal 95, no. 10 (November 2008): 4497–4511. https://doi.org/10.1529/biophysj.108.131623.
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  - Cooke, Ben, and Scott C. Schmidler. “Preserving the Boltzmann ensemble in replica-exchange molecular dynamics..” The Journal of Chemical Physics 129, no. 16 (October 2008). https://doi.org/10.1063/1.2989802.
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  - Valiaev, Alexei, Dong Woo Lim, Scott Schmidler, Robert L. Clark, Ashutosh Chilkoti, and Stefan Zauscher. “Hydration and conformational mechanics of single, end-tethered elastin-like polypeptides..” Journal of the American Chemical Society 130, no. 33 (August 2008): 10939–46. https://doi.org/10.1021/ja800502h.
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  - Colinas, Juliette, Scott C. Schmidler, Gil Bohrer, Borislav Iordanov, and Philip N. Benfey. “Intergenic and genic sequence lengths have opposite relationships with respect to gene expression..” Plos One 3, no. 11 (January 2008). https://doi.org/10.1371/journal.pone.0003670.
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  - Jiang, T., C. Tomasi, and S. C. Schmidler. “How to dispatch observers to track an evolving boundary.” 2007 1st Acm/Ieee International Conference on Distributed Smart Cameras, Icdsc, December 1, 2007, 305–12. https://doi.org/10.1109/ICDSC.2007.4357538.
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  - Schmidler, Scott C., Joseph E. Lucas, and Terrence G. Oas. “Statistical estimation of statistical mechanical models: helix-coil theory and peptide helicity prediction..” J Comput Biol 14, no. 10 (December 2007): 1287–1310. https://doi.org/10.1089/cmb.2007.0008.
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  - Valiaev, A., W. L. Dong, A. Chilkoti, S. Schmidler, and S. Zauscher. “Polypeptide-solvent interactions measured by single molecule force spectroscopy.” Materials Research Society Symposium Proceedings 898 (December 1, 2005): 92–97.
  - Schmidler, S. C. “Discussion of "A Statistical Approach to Modeling Genomic Aberrations in Cancer Cells" by Newton et. al.” Bayesian Statistics7, 2003.
  - Schmidler, S. C., J. S. Liu, and D. L. Brutlag. “Bayesian segmentation of protein secondary structure..” Journal of Computational Biology : A Journal of Computational Molecular Cell Biology 7, no. 1–2 (February 2000): 233–48. https://doi.org/10.1089/10665270050081496.
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  - Schmidler, S. C., J. S. Liu, and D. L. Brutlag. “Probabilistic modeling for protein structure prediction.” Faseb Journal 13, no. 7 (April 23, 1999): A1542–A1542.
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  - Schmidler, S. C., J. S. Liu, and D. L. Brutlag. “Bayesian protein structure prediction.” Case Studies in Bayesian Statistics 5 (1999): 363–78.
  - Wu, T. D., S. C. Schmidler, T. Hastie, and D. L. Brutlag. “Regression analysis of multiple protein structures.” Journal of Computational Biology 5, no. 3 (1998): 597–607.
  - Wu, T. D., S. C. Schmidler, T. Hastie, and D. L. Brutlag. “Regression analysis of multiple protein structures..” Journal of Computational Biology : A Journal of Computational Molecular Cell Biology 5, no. 3 (January 1998): 585–95. https://doi.org/10.1089/cmb.1998.5.585.
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  - Wu, T. D., S. C. Schmidler, T. Hastie, and D. L. Brutlag. “Modeling and superposition of multiple protein structures using affine transformations: analysis of the globins..” Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing, January 1998, 509–20.
  - Wu, T. D., T. Hastie, S. C. Schmidler, and D. L. Brutlag. “Regression analysis of multiple protein structures.” Proceedings of the Annual International Conference on Computational Molecular Biology, Recomb, January 1, 1998, 276–84.
- Conference Papers
  - Larson, G., J. L. Thorne, and S. Schmidler. “Modeling Dependence in Evolutionary Inference for Proteins.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10812 LNBI:122–37, 2018. https://doi.org/10.1007/978-3-319-89929-9_8.
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  - Wang, R., and S. C. Schmidler. “Bayesian multiple protein structure alignment.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8394 LNBI:326–39, 2014. https://doi.org/10.1007/978-3-319-05269-4_27.
    Full Text
Teaching & Mentoring
Recent Courses

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Education, Training, & Certifications

Duke Appointment History

Selected Grants

Selected Publications

Academic Articles

Conference Papers

Recent Courses