Department of Biological Sciences
and Computational Biology Department
Carnegie Mellon University
Phone: (412) 268-3971
Fax: (412) 268-7129
Office: 654B Mellon Institute
First created 11/4/02.
Last updated 5/10/16.
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
evolution, heterogeneity, and progression.
Spring 2016: 02-250/03-250 Introduction to Computational
- This is a substantially redesigned
class introduction to major computational ideas, tools, and data sets for
biological research aimed at biology 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 03-511.
- Recordings of my lectures from
02-251/03-251 are available in a
Youtube playlist based on the 2015 run of
Fall 2015: 02-512/02-712/03-512/03-712 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 computer programming.
- 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 has most recently been run by Jim Faeder
and Chris Langmead in a greatly revised
- 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
Sciences students with little or no prior computational experience. This
class was intended as a small-scale pilot for the material comprising the
new 02-250/03-250, described above.
package for inferring population substructure, history, and admixture
- HapMotif package for analyzing conserved segments
of haploid sequences.
discrete event self-assembly simulation software, a package for fast
simulation of self-assembly systems.
- SCIMP web server
implementing methods for finding maximum parsimony imperfect phylogenies
on haplotype or genotype data.
We are in the process
of migrating lab software from our local servers to a lab Github
repository. Stay tuned for
migrations of older software and future lab software releases.
Selected Recent Publications (past three years): (see my
Google Scholar page for a full citation list)
- T. Roman, L. Xie,
and R. Schwartz. "Medoidshift clustering applied to genomic bulk tumor
data" BMC Genomics, 17(S1):6, 2016.
- D. Catanzaro, S. Shackney, A. Schäffer, and
R. Schwartz. "Classifying the
progression of ductal carcinoma from single-cell sampled data via integer
linear programming: a case study."
IEEE/ACM Transactions on Computational Biology and Bioinformatics,
published online before print, 2016.
- D. Wangsa, S. A. Chowdhury, M.
Ryott, E. M. Gertz, G. Elmberger, G. Auer, E. A. Lundqvist, S. Küffer, P.
Ströbel, A. A. Schäffer, R. Schwartz, E. Munck-Wikland, T. Ried, K.
analysis of multiple FISH markers in oral tongue squamous cell carcinoma
suggests that a diverse distribution of copy number changes in associated
with poor prognosis."
International Journal of Cancer, 138(1), 2016.
- A. Subramanian and R. Schwartz.
"Reference-free inference of tumor phylogenies from single-cell
sequencing data." BMC Genomics, 16S11:S7, 2015.
- T. Roman, B. Fasy,
A. Nayyeri, and R. Schwartz. "A simplicial
complex-based approach to unmixing tumor
progression data." BMC Bioinformatics, 16:254, 2015.
- SA Chowdhury, E Gertz, D Wangsa, K
Heselmeyer-Haddad, T Ried, A Schaffer and R Schwartz. "Inferring
models of multiscale copy number evolution for
single-tumor phylogenetics." Bioinformatics
(special proceedings issue for Intelligent Systems for Molecular Biology),
- J Kang, KM Puskar, AJ Ehrlicher,
PR LeDuc, and RS Schwartz. "Structurally governed cell
mechanotransduction through multiscale modeling." Scientific Reports.
- 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,
- 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,
- 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,
- 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,