Russell Schwartz

Summary

Affiliation: Carnegie Mellon University
Country: USA

Publications

  1. ncbi request reprint Reconstructing tumor phylogenies from heterogeneous single-cell data
    Gregory Pennington
    Computer Science Department, Carnegie Mellon University, 4400 Fifth Ave, Pittsburgh, PA 15213, USA
    J Bioinform Comput Biol 5:407-27. 2007
  2. ncbi request reprint Investigating scaling effects on virus capsid-like self-assembly using discrete event simulations
    Tiequan Zhang
    Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA 15213, USA
    IEEE Trans Nanobioscience 6:235-41. 2007
  3. doi request reprint Mixed integer linear programming for maximum-parsimony phylogeny inference
    Srinath Sridhar
    Computer Science Department, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213, USA
    IEEE/ACM Trans Comput Biol Bioinform 5:323-31. 2008
  4. pmc A mixed integer linear programming model to reconstruct phylogenies from single nucleotide polymorphism haplotypes under the maximum parsimony criterion
    Daniele Catanzaro
    Graphes et Optimisation Mathématique G, O, M, Computer Science Department, Université Libre de Bruxelles U, L, B, Boulevard du Triomphe, CP 210 01, B 1050, Brussels, Belgium
    Algorithms Mol Biol 8:3. 2013
  5. pmc Frequencies of hydrophobic and hydrophilic runs and alternations in proteins of known structure
    Russell Schwartz
    Department of Biological Sciences, Carnegie Mellon University, 4400 Fifth Avenue, Pittsburgh, PA 15213, USA
    Protein Sci 15:102-12. 2006
  6. pmc Applying unmixing to gene expression data for tumor phylogeny inference
    Russell Schwartz
    Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA USA
    BMC Bioinformatics 11:42. 2010
  7. ncbi request reprint Haplotype parsing: methods for extracting information from human genetic variations
    Russell Schwartz
    Department of Biological Sciences, Carnegie Mellon University, 4400 Fifth Avenue, Pittsburgh, PA 15213, USA
    Appl Bioinformatics 3:181-91. 2004
  8. ncbi request reprint Haplotype motifs: an algorithmic approach to locating evolutionarily conserved patterns in haploid sequences
    Russell Schwartz
    Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA 15213, USA
    Proc IEEE Comput Soc Bioinform Conf 2:306-14. 2003
  9. pmc Direct maximum parsimony phylogeny reconstruction from genotype data
    Srinath Sridhar
    Computer Science Department, Carnegie Mellon University, Pittsburgh, PA, USA
    BMC Bioinformatics 8:472. 2007
  10. ncbi request reprint Stochastic off-lattice modeling of molecular self-assembly in crowded environments by Green's function reaction dynamics
    Byoungkoo Lee
    Joint Program in Computational Biology, Carnegie Mellon University and University of Pittsburgh, 654 Mellon Institute, 4400 Fifth Avenue, Pittsburgh, Pennsylvania 15213, USA
    Phys Rev E Stat Nonlin Soft Matter Phys 78:031911. 2008

Detail Information

Publications41

  1. ncbi request reprint Reconstructing tumor phylogenies from heterogeneous single-cell data
    Gregory Pennington
    Computer Science Department, Carnegie Mellon University, 4400 Fifth Ave, Pittsburgh, PA 15213, USA
    J Bioinform Comput Biol 5:407-27. 2007
    ..The results further validate the proposed computational methods by showing consistency with several previous findings on these cancers and provide novel insights into the mechanisms of tumor progression in these patients...
  2. ncbi request reprint Investigating scaling effects on virus capsid-like self-assembly using discrete event simulations
    Tiequan Zhang
    Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA 15213, USA
    IEEE Trans Nanobioscience 6:235-41. 2007
    ..We close with a consideration of mechanisms by which these obstacles may be overcome in actual viral systems...
  3. doi request reprint Mixed integer linear programming for maximum-parsimony phylogeny inference
    Srinath Sridhar
    Computer Science Department, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213, USA
    IEEE/ACM Trans Comput Biol Bioinform 5:323-31. 2008
    ..We further present a web server developed based on the exponential-sized ILP that performs fast maximum parsimony inferences and serves as a front end to a database of precomputed phylogenies spanning the human genome...
  4. pmc A mixed integer linear programming model to reconstruct phylogenies from single nucleotide polymorphism haplotypes under the maximum parsimony criterion
    Daniele Catanzaro
    Graphes et Optimisation Mathématique G, O, M, Computer Science Department, Université Libre de Bruxelles U, L, B, Boulevard du Triomphe, CP 210 01, B 1050, Brussels, Belgium
    Algorithms Mol Biol 8:3. 2013
    ..Finding the most parsimonious phylogeny for H involves solving an optimization problem, called the Most Parsimonious Phylogeny Estimation Problem (MPPEP), which is NP-hard in many of its versions...
  5. pmc Frequencies of hydrophobic and hydrophilic runs and alternations in proteins of known structure
    Russell Schwartz
    Department of Biological Sciences, Carnegie Mellon University, 4400 Fifth Avenue, Pittsburgh, PA 15213, USA
    Protein Sci 15:102-12. 2006
    ....
  6. pmc Applying unmixing to gene expression data for tumor phylogeny inference
    Russell Schwartz
    Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA USA
    BMC Bioinformatics 11:42. 2010
    ..An alternative approach uses tissue-wide measures of whole tumors to provide a detailed picture of averaged tumor state but at the cost of losing information about intra-tumor heterogeneity...
  7. ncbi request reprint Haplotype parsing: methods for extracting information from human genetic variations
    Russell Schwartz
    Department of Biological Sciences, Carnegie Mellon University, 4400 Fifth Avenue, Pittsburgh, PA 15213, USA
    Appl Bioinformatics 3:181-91. 2004
    ..The author's recent work in this area has been compiled into a set of computational tools available at http://www-2.cs.cmu.edu/~russells/software/hapmotif.html...
  8. ncbi request reprint Haplotype motifs: an algorithmic approach to locating evolutionarily conserved patterns in haploid sequences
    Russell Schwartz
    Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA 15213, USA
    Proc IEEE Comput Soc Bioinform Conf 2:306-14. 2003
    ..It further presents results on simulated data, in order to validate the method, and on two real datasets from the literature, in order to illustrate its practical application...
  9. pmc Direct maximum parsimony phylogeny reconstruction from genotype data
    Srinath Sridhar
    Computer Science Department, Carnegie Mellon University, Pittsburgh, PA, USA
    BMC Bioinformatics 8:472. 2007
    ..Hence phylogenetic applications for autosomal data must therefore rely on other methods for first computationally inferring haplotypes from genotypes...
  10. ncbi request reprint Stochastic off-lattice modeling of molecular self-assembly in crowded environments by Green's function reaction dynamics
    Byoungkoo Lee
    Joint Program in Computational Biology, Carnegie Mellon University and University of Pittsburgh, 654 Mellon Institute, 4400 Fifth Avenue, Pittsburgh, Pennsylvania 15213, USA
    Phys Rev E Stat Nonlin Soft Matter Phys 78:031911. 2008
    ....
  11. pmc Inference of tumor phylogenies from genomic assays on heterogeneous samples
    Ayshwarya Subramanian
    Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA 15213, USA
    J Biomed Biotechnol 2012:797812. 2012
    ..We demonstrate the full pipeline on simulated and real comparative genomic hybridization (CGH) data, validating its effectiveness and making novel predictions of major progression pathways and ancestral cell states in breast cancers...
  12. pmc Three-dimensional stochastic off-lattice model of binding chemistry in crowded environments
    Byoungkoo Lee
    Department of Biological Sciences and Lane Center for Computational Biology, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America
    PLoS ONE 7:e30131. 2012
    ..Simulation results over broader parameter ranges further show that the impact of molecular crowding is highly dependent on the specific reaction system examined...
  13. doi request reprint Network-based inference of cancer progression from microarray data
    Yongjin Park
    Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA 15213, USA
    IEEE/ACM Trans Comput Biol Bioinform 6:200-12. 2009
    ..Our results suggest that a network correction approach improves estimates of tumor similarity, but sophisticated network models are needed to control for the large hypothesis space and sparse data currently available...
  14. pmc Phylogenetic analysis of multiprobe fluorescence in situ hybridization data from tumor cell populations
    Salim Akhter Chowdhury
    Joint Carnegie Mellon University of Pittsburgh Ph D Program in Computational Biology, Lane Center for Computational Biology, Carnegie Mellon University, Pittsburgh, PA 15213, USA
    Bioinformatics 29:i189-98. 2013
    ..Novel algorithms for interpreting such data phylogenetically are needed, however, to reconstruct likely evolutionary trajectories from states of single cells and facilitate analysis of tumor evolution...
  15. ncbi request reprint Algorithms for efficient near-perfect phylogenetic tree reconstruction in theory and practice
    Srinath Sridhar
    Computer Science Department, Carnegie Mellon University, Pittsburgh, PA 15213, USA
    IEEE/ACM Trans Comput Biol Bioinform 4:561-71. 2007
    ....
  16. pmc A consensus tree approach for reconstructing human evolutionary history and detecting population substructure
    Ming Chi Tsai
    Joint Carnegie Mellon University University of Pittsburgh PhD Program in Computational Biology and Lane Center for Computational Biology, 4400 Fifth Avenue, Pittsburgh, PA 15213, USA
    IEEE/ACM Trans Comput Biol Bioinform 8:918-28. 2011
    ..The consensus tree approach thus provides a promising new model for the robust inference of substructure and ancestry from large-scale genetic variation data...
  17. pmc A human genome-wide library of local phylogeny predictions for whole-genome inference problems
    Srinath Sridhar
    Department of Biological Sciences, Carnegie Mellon University, USA
    BMC Genomics 9:389. 2008
    ..Making phylogenetic predictions on the scale needed for whole-genome analysis is, however, extremely computationally demanding...
  18. pmc Generalized buneman pruning for inferring the most parsimonious multi-state phylogeny
    Navodit Misra
    Department of Physics, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA
    J Comput Biol 18:445-57. 2011
    ..Our work provides the first method for provably optimal maximum parsimony phylogeny inference that is practical for multi-state data sets of more than a few characters...
  19. pmc Parameter effects on binding chemistry in crowded media using a two-dimensional stochastic off-lattice model
    Byoungkoo Lee
    654 Mellon Institute, Carnegie Mellon University of Pittsburgh Joint Program in Computational Biology, 4400 Fifth Avenue, Pittsburgh, Pennsylvania 15213, USA
    Phys Rev E Stat Nonlin Soft Matter Phys 80:041918. 2009
    ..The simulation work suggests that predictive models of crowding effects can accommodate a wider variety of parameter variations than prior theoretical models have so far achieved...
  20. pmc A parameter estimation technique for stochastic self-assembly systems and its application to human papillomavirus self-assembly
    M Senthil Kumar
    Department of Biological Sciences, Carnegie Mellon University, 4400 Fifth Avenue, Pittsburgh, PA 15213, USA
    Phys Biol 7:045005. 2010
    ..These fits provide an insight into potential assembly mechanisms of the in vitro system and give a basis for exploring how these mechanisms might vary between in vitro and in vivo assembly conditions...
  21. ncbi request reprint Discrete, continuous, and stochastic models of protein sorting in the Golgi apparatus
    Haijun Gong
    Department of Physics, Carnegie Mellon University, Pennsylvania 15213, USA
    Phys Rev E Stat Nonlin Soft Matter Phys 81:011914. 2010
    ..Experimental analysis validates a prediction of the models that altering guanine nucleotide exchange factor expression levels will modulate Golgi size...
  22. pmc Exploring the parameter space of complex self-assembly through virus capsid models
    Blake Sweeney
    Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA
    Biophys J 94:772-83. 2008
    ....
  23. pmc Robust unmixing of tumor states in array comparative genomic hybridization data
    David Tolliver
    Computer Science Department, Carnegie Mellon University, Pittsburgh PA 15213, USA
    Bioinformatics 26:i106-14. 2010
    ....
  24. doi request reprint Applying molecular crowding models to simulations of virus capsid assembly in vitro
    Gregory R Smith
    Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, Pennsylvania
    Biophys J 106:310-20. 2014
    ..These models may help us understand how complicated assembly systems may have evolved to function with high efficiency and fidelity in the densely crowded environment of the cell. ..
  25. pmc Surveying capsid assembly pathways through simulation-based data fitting
    Lu Xie
    Joint Carnegie Mellon University of Pittsburgh PhD Program in Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
    Biophys J 103:1545-54. 2012
    ..The results demonstrate the ability of such data fitting to learn very different pathway types and show some of the versatility of pathways that may exist across real viruses...
  26. doi request reprint Efficient stochastic sampling of first-passage times with applications to self-assembly simulations
    Navodit Misra
    Department of Physics, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA
    J Chem Phys 129:204109. 2008
    ..These techniques are also likely to have broader use in accelerating SSA models so as to apply them to systems and parameter ranges that are currently computationally intractable...
  27. ncbi request reprint Understanding actin organization in cell structure through lattice based Monte Carlo simulations
    Kathleen Puskar
    Department of Mechanical Engineering Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, Pennsylvania 15213, USA
    Mech Chem Biosyst 1:123-31. 2004
    ..The method and results have potential applications in cell and molecular biology as well as self-assembly for organic and inorganic systems...
  28. ncbi request reprint Computational models of molecular self-organization in cellular environments
    Philip LeDuc
    Department of Mechanical Engineering and Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA
    Cell Biochem Biophys 48:16-31. 2007
    ..In this review, we present approaches that have been undertaken from the modeling perspective to address various ways in which self-organization in the cell differs from idealized models...
  29. doi request reprint Novel multisample scheme for inferring phylogenetic markers from whole genome tumor profiles
    Ayshwarya Subramanian
    Carnegie Mellon University, Pittsburgh
    IEEE/ACM Trans Comput Biol Bioinform 10:1422-31. 2013
    ..We show an analysis of our method in comparison to other methods on both synthetic and real tumor data, which confirms its effectiveness for tumor phylogeny inference and suggests avenues for future advances. ..
  30. pmc Unified regression model of binding equilibria in crowded environments
    Byoungkoo Lee
    Department of Biological Sciences and Lane Center for Computational Biology, Carnegie Mellon University, 654 Mellon Institute, 4400 Fifth Avenue, Pittsburgh, PA, USA
    Sci Rep 1:97. 2011
    ..The work represents an important step toward the long-term goal of computationally tractable predictive models of reaction chemistry in the cellular environment...
  31. pmc Simulation study of the contribution of oligomer/oligomer binding to capsid assembly kinetics
    Tiequan Zhang
    Department of Biological Sciences and Computer Science Department, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA
    Biophys J 90:57-64. 2006
    ..The results suggest the importance of identifying the actual binding pattern if one is to build reliable models of capsid assembly or other complex self-assembly processes...
  32. pmc Simulated de novo assembly of golgi compartments by selective cargo capture during vesicle budding and targeted vesicle fusion
    Haijun Gong
    Department of Physics, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA
    Biophys J 95:1674-88. 2008
    ..This prediction was supported by a demonstration that exogenous expression of the Golgi target SNARE syntaxin-5 alters Golgi size in living cells...
  33. doi request reprint Molecular crowding shapes gene expression in synthetic cellular nanosystems
    Cheemeng Tan
    Lane Center for Computational Biology, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA
    Nat Nanotechnol 8:602-8. 2013
    ..By bridging a key gap between artificial and living cells, our work has implications for efficient and robust control of both synthetic and natural cellular circuits. ..
  34. pmc Stochastic steady state gain in a gene expression process with mRNA degradation control
    Hiroyuki Kuwahara
    The Ray and Stephanie Lane Center for Computational Biology, Carnegie Mellon University, Pittsburgh, PA 15213, USA
    J R Soc Interface 9:1589-98. 2012
    ..Because molecular reactions are intrinsically stochastic and asynchronous, these findings may have broad implications in modelling and understanding complex biological systems...
  35. pmc A comparative genomics approach to identifying the plasticity transcriptome
    Andreas R Pfenning
    Department of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
    BMC Neurosci 8:20. 2007
    ..The gene targets of these two transcription factors are of considerable interest, since they may help develop hypotheses about how neural activity is coupled to changes in neural function...
  36. ncbi request reprint Evaluating spatial constraints in cellular assembly processes using a monte carlo approach
    Kathleen Puskar
    Department of Mechanical Engineering, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213, USA
    Cell Biochem Biophys 45:195-201. 2006
    ..These conclusions have direct implications for cell shape and structure, as well as tumor cell migration...
  37. pmc Optimal haplotype block-free selection of tagging SNPs for genome-wide association studies
    Bjarni V Halldorsson
    Celera Applied Biosystems, Rockville, Maryland 20850, USA
    Genome Res 14:1633-40. 2004
    ....
  38. ncbi request reprint Robustness of inference of haplotype block structure
    Russell Schwartz
    Celera Genomics Research, Rockville, MD 20850, USA
    J Comput Biol 10:13-9. 2003
    ..For purposes of SNP selection, it seems likely that methods that do not arbitrarily impose block boundaries among correlated SNPs might perform better than block-based methods...
  39. ncbi request reprint Evolution of genes and genomes on the Drosophila phylogeny
    Andrew G Clark
    Department of Molecular Biology and Genetics, Cornell University, Ithaca, New York 14853, USA
    Nature 450:203-18. 2007
    ..These may prove to underlie differences in the ecology and behaviour of these diverse species...
  40. ncbi request reprint Epitope prediction algorithms for peptide-based vaccine design
    Liliana Florea
    Celera Applied Biosystems
    Proc IEEE Comput Soc Bioinform Conf 2:17-26. 2003
    ..The third class of methods uses sequence profiles obtained by clustering known epitopes to score candidate peptides. By integrating these methods, using a simple voting heuristic, we achieve improved accuracy over the state of the art...
  41. ncbi request reprint Algorithmic strategies for the single nucleotide polymorphism haplotype assembly problem
    Ross Lippert
    Informatics Research department, Celera Genomics, Rockville, MD 20850, USA
    Brief Bioinform 3:23-31. 2002
    ..The primary conclusion is that some important simplified variants of the problem yield tractable problems while more general variants tend to be intractable in the worst case...

Research Grants4

  1. Heterogeneous Cancer Progression from Microarray Data
    Russell S Schwartz; Fiscal Year: 2010
    ..The methods to be developed are likely to have broader applicability to solid tumor progression in general and to related problems of analyzing cell differentiation in mixed samples. ..
  2. Inferring in vivo Capsid Assembly Kinetics from in vitro by Stochastic Simulation
    Russell S Schwartz; Fiscal Year: 2010
    ..The work will also have broader relevance to understanding virus assembly in general and to developing computer models useful in a broad range of biomedical modeling applications. ..