Nikolai Slavov

Publications

• 2018
• SCoPE-MS: mass-spectrometry of single mammalian cells quantifies proteome heterogeneity during cell differentiation

  B. Budnik, E. Levy, G. Harmange, & N. Slavov. (2018)

  Genome Biology, 19, 161.
• Transformative opportunities for single-cell proteomics

  H. Specht, & N. Slavov. (2018)

  Journal of Proteome Research, 17(8), 2563-2916.
• Single cell protein analysis for systems biology

  E. Levy, & N. Slavov. (2018)

  Essays in Biochemistry, 62(4), 595-605.
• Ribosome stoichiometry

  E. P. Emmott, M. Jovanovic, & N. Slavov. (2018)

  PeerJ Preprints, 6, e26991v1.
• Automated sample preparation for high-throughput single-cell proteomics

  H. Specht, G. Harmange, D. H. Perlman, E. Emmott, Z. Niziolek, B. Budnik, & N. Slavov. (2018)

  bioRxiv.
• Quantifying homologous proteins and proteoforms

  D. Malioutov, T. Chen, E. Airoldi, J. D. Jaffe, B. Budnik, & N. Slavov. (2018)

  Molecular & Cellular Proteomics.
• Automated sample preparation for high-throughput single-cell proteomics

  H. Specht, G. Harmange, D. H. Perlman, E. Emmott, Z. Niziolek, B. Budnik, & N. Slavov. (2018)

  bioRxiv.
• DART-ID increases single-cell proteome coverage

  A. Chen, A. Franks, & N. Slavov. (2018)

  bioRxiv.
• 2017
• Kinase Activities of RIPK1 and RIPK3 Can Direct IFN-β Synthesis Induced by Lipopolysaccharide

  D. Saleh, M. Najjar, M. Zelic, S. Shah, S. Nogusa, A. Polykratis, .... (2017)

  The Journal of Immunology, 198(11), 4435-4447.
• Post-transcriptional regulation across human tissues

  A. Franks, E. Airoldi, & N. Slavov. (2017)

  PLOS Computational Biology, 13(5), 1-20.
• Quantifying homologous proteins and proteoforms

  D. Malioutov, T. Chen, J. Jaffe, E. Airoldi, S. Carr, B. Budnik, & N. Slavov. (2017)

  bioRxiv.
• Dynamic post-transcriptional regulation during embryonic stem cell differentiation

  P. R. van den Berg, B. Budnik, N. Slavov, & S. Semrau. (2017)

  bioRxiv.
• Mass-spectrometry of single mammalian cells quantifies proteome heterogeneity during cell differentiation

  B. Budnik, E. Levy, & N. Slavov. (2017)

  bioRxiv.
• 2016
• Post-transcriptional regulation across human tissues

  A. Franks, E. Airoldi, & N. Slavov. (2016)

  bioRxiv.
• Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition)

  D. J. Klionsky, K. Abdelmohsen, A. Abe, M. J. Abedin, H. Abeliovich, A. Acevedo Arozena, .... (2016)

  Autophagy, 12(1), 1–222.
• Comparative Proteomic Profiling of Divergent Phenotypes for Water Holding Capacity across the Post Mortem Ageing Period in Porcine Muscle Exudate

  A. Di Luca, R. M. Hamill, A. M. Mullen, N. Slavov, & G. Elia. (2016)

  (R. Davoli, Eds.) PLOS ONE, 11(3), e0150605.
• 2015
• De Novo Reconstruction of Adipose Tissue Transcriptomes Reveals Long Non-coding RNA Regulators of Brown Adipocyte Development

  J.  r Alvarez-Dominguez, Z. Bai, D. Xu, B. Yuan, K.  alice Lo, M.  jin Yoon, .... (2015)

  Cell Metabolism, 21(5), 764–776.
• Making the most of peer review

  N. Slavov. (2015)

  eLife, 4, 10.7554/eLife.12708.
• De Novo Reconstruction of Adipose Tissue Transcriptomes Reveals Long Non-coding RNA Regulators of Brown Adipocyte Development

  J.  r Alvarez-Dominguez, Z. Bai, D. Xu, B. Yuan, K.  alice Lo, M.  jin Yoon, .... (2015)

  Cell Metabolism, 21(6), 918.
• Differential Stoichiometry among Core Ribosomal Proteins

  N. Slavov, S. Semrau, E. Airoldi, B. Budnik, & A. van Oudenaarden. (2015)

  Cell Reports, 13(5), 865–873.
• 2014
• Convex Total Least Squares

  D. Malioutov, & N. Slavov. (2014)

  Journal of Machine Learning Research, 32(1), 109-117.
• Constant Growth Rate Can Be Supported by Decreasing Energy Flux and Increasing Aerobic Glycolysis

  N. Slavov, B.  a Budnik, D. Schwab, E.  m Airoldi, & A. van Oudenaarden. (2014)

  Cell Reports, 7(3), 705–714.
• 2013
• Calmodulin transduces $Ca^{+2}$ oscillations into differential regulation of its target proteins

  N. Slavov, J. Carey, & L. Sara. (2013)

  ACS Chemical Neuroscience, 4, 601-612.
• The Best Projects Are Least Obvious

  N. Slavov. (2013)

  The Scientist, 27(9).
• Decoupling nutrient signaling from growth rate causes aerobic glycolysis and deregulation of cell size and gene expression

  N. Slavov, & D. Botstein. (2013)

  Molecular Biology of the Cell, 24(2), 157–168.
• 2012
• How to Regulate a Gene: To Repress or to Activate?

  N. Slavov, & A. van Oudenaarden. (2012)

  Molecular Cell, 46(5), 551–552.
• A conserved cell growth cycle can account for the environmental stress responses of divergent eukaryotes

  N. Slavov, E. M. Airoldi, A. van Oudenaarden, & D. Botstein. (2012)

  Molecular Biology of the Cell, 23(10), 1986–1997.
• 2011
• Coupling among growth rate response, metabolic cycle, and cell division cycle in yeast

  N. Slavov, & D. Botstein. (2011)

  Molecular Biology of the Cell, 22(12), 1997–2009.
• Metabolic cycling without cell division cycling in respiring yeast

  N. Slavov, J. Macinskas, A. Caudy, & D. Botstein. (2011)

  Proceedings of the National Academy of Sciences, 108(47), 19090–19095.
• 2010
• Inference of Sparse Networks with Unobserved Variables. Application to Gene Regulatory Networks

  N. Slavov. (2010)

  In Y. W. Teh & D. M. Titterington (Eds.), Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, AISTATS 2010, Chia Laguna Resort, Sardinia, Italy, May 13-15, 2010 (Vol. 9, p. 757–764)JMLR.org.
• Universality, specificity and regulation of S. cerevisiae growth rate response in different carbon sources and nutrient limitations

  N. Slavov. (2010)

  Princeton University.
• Metabolic cycling in single yeast cells from unsynchronized steady-state populations limited on glucose or phosphate

  S. J. Silverman, A. A. Petti, N. Slavov, L. Parsons, R. Briehof, S. Y. Thiberge, .... (2010)

  Proceedings of the National Academy of Sciences, 107(15), 6946–6951.
• 2009
• Correlation signature of the macroscopic states of the gene regulatory network in cancer

  N. Slavov, & K. A. Dawson. (2009)

  Proceedings of the National Academy of Sciences, 106(11), 4079–4084.
• 2005
• Multi-Class Biclustering and Classification Based on Modeling of Gene Regulatory Networks

  I. Tagkopoulos, N. Slavov, & S. Y. Kung. (2005)

  In Fifth IEEE Symposium on Bioinformatics and Bioengineering (BIBE'05) (p. 89–96)Presented at the Fifth IEEE Symposium on Bioinformatics and Bioengineering (BIBE'05), IEEE.
• Multi-Class Biclustering and Classification Based on Modeling of Gene Regulatory Networks

  I. Tagkopoulos, N. Slavov, & S. - Y. Kung. (2005)

  In Fifth IEEE International Symposium on Bioinformatic and Bioengineering (BIBE 2005), 19-21 October 2005, Minneapolis, MN, USA (p. 89–96)IEEE Computer Society.