Recent Publications

If you need preprints, please send an e-mail to [email protected] or contact the corresponding author.

• J. Abante, S. Kambhampati, A. P. Feinberg, and J. Goutsias, Estimating DNA methylation potential energy landscapes from nanopore sequencing data, Scientific Reports, Vol. 11, No. 21619, 2021

• M. Koldobskiy, et al, Converging genetic and epigenetic drivers of paediatric acute lymphoblastic leukemia identified by an information-theoretic analysis, Nature Biomedical Engineering, Vol. 5, 360-376, 2021
  
  
• J. Abante and J. Goutsias, CpelTdm.jl: a Julia package for targeted differential
  DNA methylation analysis, bioRxiv, 2020.
  
  
• J. Abante, Y. Fang, A. P. Feinberg, and J. Goutsias, Detection of haplotype-dependent allele-specific
  DNA methylation in WGBS data, Nature Communications, Vol. 11, No. 5238, pp. 1-13, 2020
  
  
• F. E. Garrett-Bakelman, et al, The NASA twins study: A multidimensional analysis of a year-long human spaceflight, Science, Vol. 364, No. 6436, 2019
  

• G. Jenkinson, J. Abante, M. A. Koldobskiy, A. P. Feinberg, and J. Goutsias
  Ranking genomic features using an information-theoretic measure of epigenetic discordance, BMC Bioinformatics, Vol. 20 No. 175, 2019
  

• G. Jenkinson, J. Abante, A. P. Feinberg, and J. Goutsias, An information-theoretic approach to the modeling and analysis of whole-genome bisulfite sequencing data, BMC Bioinformatics, Vol. 19, No. 87, 2018
  

• H. Nakamura, A. A. Lee, A. S. Afshar, S. Watanabe, E. Rho, S. Razavi, A. Suarez, Y.-C. Lin, M. Tanigawa, B. Huang, R. DeRose, D. Bobb, W. Hong, S. B. Gabelli, J. Goutsias, and T. Inoue, Intracellular production of hydrogels and synthetic RNA granules by multivalent molecular interactions, Nature Materials, Vol. 17, No. 1, pp. 79-89, 2018

• G. Jenkinson, E. Pujadas, J. Goutsias, and A. P. Feinberg, Potential energy landscapes identify the information-theoretic nature of the epigenome, Nature Genetics, Vol. 49, No. 5, pp. 719-729, 2017
  

• A. S. Afshar, J. Xu, and J. Goutsias, Integrative identification of deregulated miRNA/TF-mediated gene regulatory loops and networks in prostate cancer, PLoS One, Vol. 9, No. 6, e100806, 2014.
  

• G. Jenkinson and J. Goutsias, Intrinsic noise induces critical behavior in leaky Markovian networks leading to avalanching, PLoS Computational Biology, Vol. 10, No. 1, e1003411, 2014.
  
  
• G. Jenkinson and J. Goutsias, Statistically testing the validity of analytical and computational approximations to the chemical master equation, The Journal of Chemical Physics, Vol. 138, No. 204108, pp.1-19, 2013.

• J. Goutsias and G. Jenkinson, Markovian dynamics on complex reaction networks, Physics Reports, Vol. 529, No. 2, pp. 199-264, 2013
  

• G. Jenkinson and J. Goutsias, Numerical integration of the master equation in some models of stochastic epidemiology, PLoS One, Vol. 7, No. 5, e36160, 2012.

• G. Jenkinson and J. Goutsias, Dynamics on networks: chemical reactions as a unifying framework, Conference Record of the 45th Asilomar Conference on Signals, Systems, and Computers, pp. 1031-1035, Pacific Grove, California, November 6-9, 2011.

• G. Jenkinson and J. Goutsias, Thermodynamically consistent model calibration in chemical kinetics, BMC Systems Biology, Vol. 5, 64, 2011.
  
  
• H.-X. Zhang and J. Goutsias, Reducing experimental variability in variance-based sensitivity analysis of biochemical reaction systems, The Journal of Chemical Physics, Vol. 134, No. 114105, pp.1-16, 2011.
  
  
• W. G. Jenkinson and J. Goutsias, A screening method for dimensionality reduction in biochemical reaction system calibration, Proceedings of the 9th IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS), Cold Spring Harbor Laboratory, New York, November 10-12, 2010.
  
  
• G. Jenkinson, X. Zhong, and J. Goutsias, Thermodynamically consistent Bayesian analysis of closed biochemical reaction systems, BMC Bioinformatics, Vol. 11, 547, 2010. To download a correctly typeset pdf file of this paper, click here.

• H.-X. Zhang, Probabilistic Sensitivity Analysis of Biochemical Reaction Systems. Ph.D. Dissertation, The Johns Hopkins University, Baltimore, MD, 2010.

• W. Garrett Jenkinson and J. Goutsias,On constructing thermodynamically consistent parametrizations of kinetic models, Proceedings of the 2010 IEEE International Conference on Bioinformatics and Bioengineering, pp. 214-219, Philadelphia, Pennsylvania, May 31 - June 3, 2010.

• H.-X. Zhang and J. Goutsias, A comparison of approximation techniques for variance-based sensitivity analysis of biochemical reaction systems, BMC Bioinformatics, Vol. 11, 246, 2010. To download a correctly typeset pdf file of this paper, click here.

• H.-X. Zhang, W. P. Dempsey, Jr., and J. Goutsias, Probabilistic sensitivity analysis of biochemical reaction systems, The Journal of Chemical Physics, Vol. 131, No. 094101, pp. 1-20, 2009. Also, in Virtual Journal of Biological Physics Research, Vol. 18, Issue 6, 2009.

• J. Goutsias and N. H. Lee, Computational and experimental approaches for modeling gene regulatory networks, Current Pharmaceutical Design, Vol. 13, No. 14, pp. 1415-1436, 2007.

• J. Goutsias, Classical versus stochastic kinetics modeling of biochemical reaction systems, Biophysical Journal, Vol. 92, pp. 2350-2365, 2007.

• J. Goutsias and S. Kim, Stochastic transcriptional regulatory systems with time delays: A mean-field approximation,
  Journal of Computational Biology, Vol. 13, No. 5, pp. 1049-1076, 2006.

• J. Goutsias, A hidden Markov model for transcription regulation in single cells, IEEE/ACM Transactions on Computational Biology and Bioinformatics, Vol. 3, No. 1, pp. 57-71, 2006.

• J. Goutsias, Quasi-equilibrium approximation of stochastic biochemical systems for transcription regulation, 2005 IEEE International Workshop on Genomic Signal Processing and Statistics, Newport, Rhode Island, May 22-24, 2005.

• J. Goutsias, Quasiequilibrium approximation of fast reaction kinetics in stochastic biochemical systems, The Journal of Chemical Physics, Vol. 122, No. 184102, pp. 1-15, 2005. Also, in Virtual Journal of Biological Physics Research, Vol. 9, Issue 10, 2005.

• J. Goutsias and S. Kim, A Nonlinear Discrete Dynamical Model for Transcriptional Regulation: Construction and Properties, Biophysical Journal, Vol. 86, pp. 1922-1945, 2004.