Department of Biological Sciences
Lane Center for Computational Biology
Carnegie Mellon University
Phone: (412) 268-3971
Fax: (412) 268-7129
Office: 654B Mellon Institute
First created 11/4/02.
Last updated 12/20/14.
My research interests are in the area of computational molecular
biology and the modeling and simulation of biological systems. My group
is currently working most actively on three topics: simulation methods
for macromolecular assembly systems, with special focus on more
realistic models of assembly in cellular environments; methods for
analysis of human genetic variation data, most recently focused on
phylogenetics and population substructure analysis; and application of
phylogenetic methods to study cancer progression.
Spring 2015: 02-250/03-250 Introduction to Computational Biology
This is a substantially redesigned class introduction to major
computational ideas, tools, and data sets for biological research aimed
students with little or no prior computational experience. The class
can be taken either as a full-semester version, 02-250/03-250, that covers
genomics, modeling, and image informatics, or as either of two
half-semester mini-classes, 02-251/03-251 for the genomics material or 02-252/03-252
for modeling and image informatics. Students with prior training in
programming, algorithms, and data structures should instead consider
Fall 2014: 03-512/03-712/15-507/15-871 Computational Methods for Biological Modeling and Simulation
- This is a class on models, algorithms, and numerical methods used
in modeling and simulating biological systems. The class is aimed at
graduate students and advanced undergraduates interested in developing
new methods and tools for computational biology. It assumes
introductory knowledge of biology, algorithms and data structures, and
course web page for more information.
I previously developed 03-101C, Computational Resources for Biology, a
first-year mini class for biology students devoted to hands-on work with
on-line tools and databases for genomics. The material of this class
was subsumed and expanded to create 03-311.
I also co-developed 02-730, Cell and Systems
Modeling, a core class of our n Ph.D. Program in Computational
Biology jointly run by the University of Pittsburgh and Carnegie
Mellon. I co-taught this class with Joel Stiles and Ivan Maly in Spring
2007 and Spring 2007. It is now taught by Joel Stiles and James
I also previously taught 03-311, the non-programming version of
Introduction to Computational Biology. This was a 6-unit mini class
intended to provide an introduction to major
computational ideas, tools, and data sets aimed primarily at Biological
students with little or no prior computational experience. This class
was intended as a small-scale pilot for the material comprising the new
03-311, described above.
package for inferring population substructure, history, and admixture events.
package for analyzing conserved segments of haploid sequences.
DESSA discrete event self-assembly simulation software, a package for fast simulation of
SCIMP web server implementing methods for finding maximum parsimony imperfect phylogenies on haplotype or genotype data.
Selected Recent Publications (past three years): (Full Publication List)
S. E. Shackney, S. A. Chowdhury, R. Schwartz. "A novel subset of human tumors that simultaneously overexpress multiple E2F responsive genes found in breast, ovarian, and prostate cancer." Cancer Informatics, 13(S5):89, 2014.
K. Heselmeyer-Haddad, L.Y. Berroa Garcia, A. Bradley, L. Hernandez, Y. Hu, J.K. Habermann, C. Dumke, C. Thorns, S. Perner, E. Pestova, C. Burke, S.A. Chowdhury, R. Schwartz, A.A. Schaffer, P. Paris, T. Ried. "Single-cell genetic analysis reveals insights into clonal development of prostate cancers and indicates loss of PTEN as a marker of poor prognosis", American Journal of Pathology, 184(10):2671-2686, 2014.
C. Tan, R. Schwartz, L. You. "Phenotypic signatures arising from unbalanced bacterial growth," PLoS Computational Biology, 10(8):e1003751, 2014.
H. Ashktorab, M. Daremipouran, J. Devaney, S. Varma, H. Rahi, E., Lee, B. Shokrani, R. Schwartz, M. Nickerson, H. Brim. "Identification of novel mutations by exome sequencing in African American colorectal cancer patients", Cancer, 121(1):34-42, 2014.
S.A. Chowdhury, S.E. Shackney, K. Heselmeyer-Haddad, T. Ried, A. Schaffer, R. Schwartz. "Algorithms to Model Single Gene, Single Chromosome, and Whole Genome Copy Number Changes Jointly in Tumor Phylogenetics," PLoS Computational Biology, 10(7):e1003740, 2014.
G.R. Smith, L. Xie, B. Lee, and R. Schwartz. "Applying cellular crowding models to simulations of capsid assembly in vitro." Biophysical Journal, 106(1):310-320, 2014.
M.-C. Tsai, G. Blelloch, R. Ravi, and R. Schwartz. "Coalescent-based Method for Learning Parameters of Admixture Events from Large-Scale Genetic Variation Data," IEEE/ACM Transactions on Computational Biology and Bioinformatics, 10(5):1137-1149, 2013. (extended version of ACM-BCB conference paper)
A. Subramanian, S. Shackney, and R. Schwartz. "Novel multi-sample scheme for inferring phylogenetic markers from whole genome tumor profiles." IEEE/ACM Transactions on Computational Biology and Bioinformatics, 10(6):1422-1431, 2013. (extended version of ISBRA conference paper)
C. Tan, S. Saurabh, M. Bruchez, R. Schwartz, and P. LeDuc. "Molecular crowding shapes gene expression in synthetic cellular nanosystems." Nature Nanotechnology, 8(8):602-608, 2013.
S. A. Chowdhury, S. E. Shackney, K. Heselmeyer-Haddad, T. Ried, A. A. Schaeffer, R. Schwartz. "Phylogenetic analysis of multiprobe fluorescence in situ hybridization data from tumor cell populations." Bioinformatics (proceedings issue for ISMB 2013), 29(13):i189-i198, 2013.
D. Catanzaro, R. Ravi, and R. Schwartz. "A mixed integer linear programming model to reconstruct phylogenies from single nucleotide polymorphism haplotypes under the maximum parsimony criterion." Algorithms for Molecular Biology, 8:3, 2013.
K. Heselmeyer-Haddad, L. Y. Berroa Garcia, A. Bradley, C. Ortiz-Melendez, W.-J. Lee, R. Christensen, S. A. Prindiville, K. A. Calzone, P. W. Soballe, Y. Hu, S. A. Chowdhury, R. Schwartz, A. A. Schaeffer, and T. Ried. "Single-cell genetic analysis of ductal carcinoma in situ and invasive breast cancer reveals enormous tumor heterogeneity, yet conserved genomic imbalances and gain of MYC during progression." American Journal of Pathology, 181(11):1807-1822, 2012.
L. Xie, G. Smith, X. Feng, and R. Schwartz. "Surveying capsid assembly pathways through simulation-based data fitting." Biophysical Journal, 103:1545-1554, 2012.
W. C. Ruder, C.-P. D. Hsu, B. D. Edelman, R. Schwartz, and P. R. LeDuc "Biological colloid engineering: self-assembly of dipolar ferromagnetic chains in a functionalized biogenic ferrofluid." Applied Physics Letters, 101:063701, 2012.
A. Subramanian, S. Shackney, and R. Schwartz. "Inference of tumor phylogenies from genomic assays on heterogeneous samples." Journal of Biomedicine and Biotechnology, 2012:798812, 2012. (extended version of 2011 ACM/BCB conference paper)
H. Kuwahara and R. Schwartz. "Stochastic steady state gain in a gene expression process with mRNA degradation control." Journal of the Royal Society Interface, 9:1589-1598, 2012.
B. Lee, P. R. LeDuc, and R. Schwartz. "Three-dimensional stochastic off-lattice model of binding chemistry in crowded environments." PLoS One, 7(1): e30131, 2012.
N. S. Wren, R. Schwartz, and K. N. Dahl. "Modeling nuclear blebs in a nucleoskeleton of independent filament networks." Cellular and Molecular Bioengineering, 5(1):73-81, 2012.