School of Computer Science › Ray and Stephanie Lane Computational Biology Department › People › Russell Schwartz

Russell Schwartz

Professor and Head, Ray and Stephanie Lane Computational Biology Department

Address:

Ray and Stephanie Lane Computational Biology Department, SCS

Carnegie Mellon University

5000 Forbes Avenue

Pittsburgh, PA 15213

Gates Hillman Center Room 7723

Work Phone: 412-268-3971

Administrative Assistant: Erin Driskill

Computational Cancer Research Website

Dr. Schwartz works broadly on models and simulations of biological systems, including work in computational genomics, phylogenetics, population genetics, and biophysics. The largest area of his lab’s work in recent years has been computational cancer biology, with specific focus on algorithmic development related to clonal evolution in cancers and resulting tumor heterogeneity. His lab also pursues work in stochastic simulation, with primary focus on models and model inference methods for simulating complex self-assembly dynamics.

Lab Members

Nishat Bristy

Ph.D. Student

Lanting Li

Ph.D. Student (co-advised by Oana Carja)

Thomas Rachman

Ph.D. Student (co-advised by Oana Carja)

Arjun Srivatsa

Ph.D. Student

Highlighted Publications

A. Srivatsa and R. Schwartz. “Optimizing design of genomic studies for clonal evolution analysis,” Bioinformatics Advances, 4(1):vbae193, 2024.

C. Brooksbank, M.D. Brazas, N. Mulder, R. Schwartz, V. Ras, S.L. Morgan, M. Lloret-Llinares, P. Carvajal-López, L. Larcombe, A. Ghouila, T. Hancocks, V. Satagopam, J. De Las Rivas, G. Mazandu, B. Gaeta. “The ISCB competency framework v. 3: a revised and extended standard for bioinformatics education and training”. Bioinformatics Advances, 4(1):vba126, 2024.

T. Rachman, D. Bartlett, W. LaFramboise, P. Wagner, R. Schwartz, O. Carja. “Modeling the effect of spatial structure on solid tumor evolution and ctDNA composition.” Cancers, 16(5), 2024.
4. C.-H. Wu, S. Joshi, W. Robinson, P. F. Robbins, R. Schwartz, S. C. Sahinalp and S. Malikic. “Determining optimal placement of copy number aberration impacted single nucleotide variants in a tumor progression history.” Proc. Research in Computational Molecular Biology (RECOMB), 2024.

E.B. Işık, M.D. Brazas, R. Schwartz, B. Gaeta, P. M. Palagi, C.W. G. van Gelder, P. Suravajhala, H. Singh, S.L. Morgan, H. Zahroh, M. Ling, V.P. Satagopam, A. McGrath, K. Nakai, N. Mulder, C. SchönbachY. Zheng, J. De Las Rivas, A. M. Khan. “Grand challenges in bioinformatics education and training.” Nature Biotechnology, 41:1171-1174, 2023.

A. Srivatsa, H. Lei, and R. Schwartz. “A clonal evolution simulator for planning somatic evolution studies,” Journal of Computational Biology, 30(8):831-847, 2023.

Y. Tao, X. Ma, D. Palmer, R. Schwartz, X. Lu, H. Osmanbeyoglu. “Interpretable deep learning for chromatin-informed inference of transcriptional programs driven by somatic alterations across cancers” Nucleic Acids Research, 50(19):10869-10881, 2022.

X. Fu, H. Lei, Y. Tao, and R. Schwartz. “Reconstructing tumor clonal lineage trees incorporating single nucleotide variants, copy number alterations, and structural variations.” Bioinformatics (ISMB proceedings issue), 38 (Supplement_1), i125-i133, 2022.

H. Lei, E. M. Gertz, A. A. Schaeffer, X. Fu, Y. Tao, K. Heselmeyer-Haddad, I. Torres, G. Li, L. Xu, Y. Hu, K. Wu, X. Shi, M. Dean, T. Ried, R. Schwartz. “Tumor heterogeneity assessed by sequencing and fluorescence in situ hybridization (FISH) data.” Bioinformatics, 37 (24), 4704-4711, 2021.

Y. Tao, A. Rajaraman, X. Cui, Z. Cui, J. Eaton, H. Kim, J. Ma. and R. Schwartz. “Assessing the contribution of tumor mutational phenotypes to cancer progression risk.” PLoS Computational Biology, 17(3), e100877, 2021.

Google Scholar

PubMed

Highlighted Software

TUSV-Ext - (Clonal lineage reconstruction from SNV, SV, and CNA data)

SC-TUSV-ext - (TUSV-ext for single-cell sequence)

MosaicSim - (Versatile clona evolution simulator)

FISH_deconvolution- (Deconvolution from bulk and single-cell DNA-seq plus FISH)

RADS - (Deconvolution from bulk and single-cell-RNA seq)