1. Reductionism Is Dead: Long Live Reductionism! Systems Modeling Needs Reductionist Experiments. Faeder JR, Morel PA. Biophysical journal. 2016; 110(8):1681-3.

  2. Unbiased Rare Event Sampling in Spatial Stochastic Systems Biology Models Using a Weighted Ensemble of Trajectories. Donovan RM, Tapia JJ, Sullivan DP, Faeder JR, Murphy RF, Dittrich M, Zuckerman DM. PLoS computational biology. 2016; 12(2):e1004611.

  3. Harris, LA, Hogg, JS, Tapia, JJ, Sekar, JAP, Gupta, S, Korsunsky, I, Arora, A, Barua, D,  Sheehan, RP, and Faeder, JR (2016) BioNetGen 2.2: Advances in Rule-Based Modeling. Bioinformatics, doi:10.1093/bioinformatics/btw469. (full text) (reprint).
  1. The eighth q-bio conference: meeting report and special issue preface. Hlavacek WS, Gnanakaran S, Munsky B, Wall ME, Faeder JR, Jiang Y, Nemenman I, Resnekov O. Physical biology. 2015; 12(6):060401.

  2. Modeling for (physical) biologists: an introduction to the rule-based approach. Chylek LA, Harris LA, Faeder JR, Hlavacek WS. Physical biology. 2015; 12(4):045007. NIHMSID: NIHMS710704

  3. Cutting Edge: Differential Regulation of PTEN by TCR, Akt, and FoxO1 Controls CD4+ T Cell Fate Decisions. Hawse WF, Sheehan RP, Miskov-Zivanov N, Menk AV, Kane LP, Faeder JR, Morel PA. Journal of immunology (Baltimore, Md. : 1950). 2015; 194(10):4615-9. NIHMSID: NIHMS672845

  1. Hogg JS, Harris LA, Stover LJ, Nair NS, Faeder JR (2014) Exact hybrid particle/population simulation of rule-based models of biochemical systems PLoS Comput Biol Apr 3; 10(4):e1003544.
  2. Nemenman I, Faeder JR, Gnanakaran S, Hlavacek WS, Munsky B, Wall ME, Jiang Y (2014) The Seventh q-bio Conference: meeting report and preface Phys Biol 11(4):040301.
  3. Morel PA, Faeder JR, Hawse WF, Miskov-Zivanov N (2014) Modeling the T cell immune response: a fascinating challenge J Pharmacokinet Pharmacodyn [Epub ahead of print]
  4. Wenskovitch JE Jr, Harris LA, Tapia JJ, Faeder JR, Marai GE (2014) MOSBIE: a tool for comparison and analysis of rule-based biochemical models BMC Bioinformatics 15(1):316. [Epub ahead of print]
  1. Nemenman I, Gnanakaran S, Munsky B, Wall ME, Jiang Y, Hlavacek WS, Faeder JR (2013) Special section dedicated to The Sixth q-bio Conference: meeting report and preface. Phys Biol Jun;10(3):030301. [JIF=3.109]
  2. Price I, Ermentrout B, Zamora R, Wang B, Azhar N, Mi Q, Constantine G, Faeder JR, Luckhart S, Vodovotz Y (2013) In vivo, in vitro, and in silico studies suggest a conserved immune module that regulates malaria parasite transmission from mammals to mosquitoes. J Theor Biol pii: S0022-5193(13)00258-0. [JIF=2.371]
  3. Donovan RM, Sedgewick AJ, Faeder JRZuckerman DM (2013) Efficient stochastic simulation of chemical kinetics networks using a weighted ensemble of trajectories J Chem Phys 139(11):115105.
  4. Chylek LA, Harris LA, Tung CS, Faeder JR, Lopez CF, Hlavacek WS (2013) Rule-based modeling: a computational approach for studying biomolecular site dynamics in cell signaling systems Wiley Interdiscip Rev Syst Biol Med Sept 30 [Epub ahead of print].
  5. Miskov-Zivanov N, Turner MS, Kane LP, Morel PA, Faeder JR (2013) The duration of T cell stimulation is a critical determinant of cell fate and plasticity Sci Signal 6(300):ra97.
  1. Sekar JA, Faeder JR (2012) Rule-based modeling of signal transduction: a primer. Methods Mol Biol 880:139-218.
  2. Smith AM, Xu W, Sun Y, Faeder JR, Marai GE. (2012). RuleBender: integrated modeling, simulation and visualization for rule-based intracellular biochemistry. BMC Bioinformatics. 13 Suppl 8:S3.
  1. RULEBENDER: A Visual Interface for Rule-Based Modeling
    W. Xu, A. M. Smith, J. R. Faeder,* and G. E. Marai*
    Bioinformatics, 27, 1721-2, 2011. (link). (preprint)
    *Corresponding authors
  2. Efficient modeling, simulation and coarse-graining of biological complexity with NFsim
    M. W. Sneddon, J. R. Faeder, and T. Emonet
    Nature Methods., 8, 177-183, 2011. (link)
  3. Guidelines for visualizing and annotating rule-based models
    Chylek LA, Hu B, Blinov ML, Emonet T, Faeder JR, Goldstein B, Gutenkunst RN, Haugh JM, Lipniacki T, Posner RG, Yang J, Hlavacek WS
    Mol. Biosyst., 7, 2779-95, 2011. (pdf)
  4. Selected papers from the Fourth Annual q-bio Conference on Cellular Information Processing
    Nemenman I, Faeder JR, Hlavacek WS, Jiang Y, Wall ME, Zilman A.
    Phys. Biol., 8, 050301, 2011. (link)
  5. Synergism between different germinant receptors in the germination of Bacillus subtilis spores
    Yi X, Liu J, Faeder JR, Setlow P.
    J. Bacteriol., 193, 4664-71, 2011 (link)
  6. Toward a comprehensive language for biological systems
    J. R. Faeder
    BMC Biol., 9, 68, 2011. (link)
  7. Rule-Based Modeling of Signal Transduction: A Primer
    J. A. P. Sekar and J. R. Faeder
    Meth. Mol. Biol., in press. (preprint)
  1. Modeling multivalent ligand-receptor interactions with steric constraints on configurations of cell-surface receptor aggregates
    M. I. Monine , R. G. Posner, P. B. Savage, J. R. Faeder, and W. S. Hlavacek. Biophys. J., 98, 48-56, 2010.
  2. Simulations of ICl(CO2)n photodissociation: Effects of structure, excited state charge flow, and solvent dynamics
    J. R. Faeder and R. Parson. J. Phys. Chem. A, 114, 1347-1356, 2010.
  3. Use of carbon fate maps to determine steady-state metabolic fluxes and metabolite pool sizes from 13C-labeling dynamics
    F. Mu, A. L. Bauer, J. R. Faeder and W. S. Hlavacek. In Handbook of Chemoinformatics Algorithms (J.-L. Faulon and A. Bender, Editors) Chapman & Hall/CRC Press, Boca Raton, FL, Ch. 15. ISBN: 978-1420082920, 2010.
  4. Translational Systems Approaches to the Biology of Inflammation and Healing
    Y. Vodovotz, G. Constantine, J. Faeder, Q. Mi, J. Rubin, J. Bartels, J. Sarkar, R. H. Squires, D. O. Okonkwo, J. Gerlach, R. Zamora, S. Luckhart, B. Ermentrout, and G. An. Immunopharm. Immunotoxicol.,32, 181-95, 2010.
  5. Shaping the response: The role of FcεRI and Syk expression levels in mast cell signaling
    A. Nag, J. R. Faeder, and B. Goldstein. IET. Syst. Biol., 4, 334-47, 2011. (link)
  6. Analysis and Verification of the HMGB1 Signaling Pathway
    H. Gong, P. Zuliani, A. Komuravelli, J. R. Faeder, and E.M. Clarke.BMC Bioinformatics, 11, S10 (13 pages). (link) Best paper award
  7. Computational Modeling and Verification of Signaling Pathways in Cancer
    H. Gong, P. Zuliani, A. Komuravelli, J. R. Faeder, and E.M. Clarke. Proceedings of the 2010 Algebraic and Numerical Biology (ANB) Conference.
  1. Rule-Based Modeling of Biochemical Systems with BioNetGen
    J. R. Faeder, M. L. Blinov, and W. S. Hlavacek
    Methods Mol. Biol., 500, 113-167, 2009. (pdf) (link)
  2. Detailed qualitative dynamic knowledge representation using a BioNetGen model of TLR-4 signaling and preconditioning
    G. C. An and J. R. Faeder
    Math. Biosci., 217, 53-63, 2009. (pdf) (link)
  3. Aggregation of membrane proteins by cytosolic cross-linkers: Theory and simulation of the LAT-Grb2-Sos1 system
    A. Nag, M. I. Monine, J. R. Faeder, and B. Goldstein
    Biophys. J., 96, 2604-2623, 2009. (link)
  4. Simulation of large-scale rule-based models
    J. Colvin, M. I. Monine, J. R. Faeder, W. S. Hlavacek, D. D. Von Hoff, and R. G. Posner
    Bioinformatics, 25, 910-917, 2009. (pdf) (link)
  5. A bipolar clamp mechanism for activation of Jak-family protein tyrosine kinases
    D. Barua, J. R. Faeder, and J. M. Haugh
    PLoS Comput. Biol. 2009, 5, e1000364, 2009. (link)
  6. GetBonNie for building, analyzing and sharing rule-based models
    B. Hu, G. M. Fricke, J. R. Faeder, R. G. Posner, and W. S. Hlavacek
    Bioinformatics, 25, 1457-1460, 2009. (link)
  7. Workshop Report: Modeling the Molecular Mechanism of Bacterial Spore Germination and Elucidating Reasons for Germination Heterogeneity
    K. Indest, W. Buchholz, J. Faeder, and P. Setlow
    J. Food. Sci., 74, R73-8, 2009. (preprint-pdf)
  8. The Complexity of Cell Signaling and the Need for a New Mechanics
    W. S. Hlavacek and J. R. Faeder
    Sci. Signaling, 2, pe46, 2009. (pdf).
  9. Compartmental Rule-Based Modeling of Biochemical Systems
    L. A. Harris, J. S. Hogg, and J. R. Faeder
    Proceedings of the 2009 Winter Simulation Conference (WSC), in press. (invited) (pdf)
  10. Toward a quantitative theory of intrinsic disorder and function
    J. Liu, J. R. Faeder, and C. J. Camacho
    Proc. Nat. Acad. Sci. USA, 106, 19819-23, 2009. (F1000 “Must Read”)
  1. Kinetic proofreading model
    B. Goldstein, D. Coombs, J. R. Faeder and W. S. Hlavacek
    Adv. Exp. Med. Biol., 640, 82-94, 2008.
  2. Statistical model checking in BioLab: Applications to the automated analysis of T-cell receptor signaling pathway
    E. M. Clarke, J. R. Faeder, L. A. Harris, C. J. Langmead, A. Legay, and S. K. Jha
    Proceedings of The 6th Conference on Computational Methods in Systems Biology (CMSB), 2008.
  3. Domain-oriented reduction of rule-based network models
    N. M. Borisov, A. S. Chistopolsky, J. R. Faeder, and B. N. Kholodenko
    IET Syst. Biol., 2, 342-351, 2008.
    (pdf) (link)
  4. Kinetic Monte Carlo Method for Rule-based Modeling of Biochemical Networks
    J. Yang, M. I. Monine, James R. Faeder, and W. S. Hlavacek
    Phys. Rev. E, 78, 031910, 2008.
    (pdf) (warning: crashes Mac Preview)
  5. Stochastic effects and bistability in T cell receptor signaling
    T. Lipniacki, B. Hat, J. R. Faeder, & W. S. Hlavacek.
    J. Theor. Biol., 254, 110-122, 2008.
  6. Computational models of tandem Src homology 2 domain interactions and application to phosphoinositide 3-kinase
    D. Barua, J. R. Faeder, J. M. Haugh,“
    J. Biol. Chem., 283, 7338-45, 2008.
  7. Translational systems biology:  Introduction of an engineering approach to the pathophysiology of the burn patient
    G. An, J. Faeder, and Y. Vodovotz
    J. Burn Care Res.
    , 29, 277-85, 2008.
  1. Q-bio 2007: a watershed moment in modern biology
    J. S. Edwards, J. R. Faeder, W. S. Hlavacek Y. Jiang, I. Nemenman, and M. E. Wall
    Mol. Syst. Biol., 3, 148, 2007.
  2. Kinetic proofreading of ligand-FcεRI interactions may persist beyond LAT phosphorylation
    C. Torigoe, J. R. Faeder, J. M. Oliver, and B. Goldstein
    J. Immunol., 178, 3530-3535, 2007.
  3. Structure-based kinetic models of modular signaling protein function: Focus on Shp2
    D. Barua, J. R. Faeder, and J. M. Haugh
    Biophys. J., 92, 2290-2300, 2007.
  4. Carbon fate maps for metabolic reactions
    F. Mu, R. F. Williams, P. J. Unkefer, C. J. Unkefer, J. R. Faeder, and W. S. Hlavacek
    , 23, 3193-3199, 2007.
  1. Graph theory for rule-based modeling of biochemical networks
    M. L. Blinov, J. Yang, J. R. Faeder and W. S. Hlavacek
    Lect. Notes Comput. Sci. 4230, 89-106, 2006.
  2. A network model of early events in epidermal growth factor receptor signaling that accounts for combinatorial complexity
    M. L. Blinov, J. R. Faeder, B. Goldstein, and W. S. HlavacekBiosystems, 83, 136-151, 2006.
  3. Depicting signaling cascades
    M. L. Blinov, J. Yang, J. R. Faeder, and W. S. Hlavacek
    Nat. Biotechnol., 24, 137-138, 2006.
  4. Rules for modeling signal-transduction systems
    W. S. Hlavacek, J. R. Faeder, M. L. Blinov, R. G. Posner, M. Hucka, and W. Fontana.
    Sci. STKE., 2006, re6, 2006.


  1. Graphical rule-based representation of signal-transduction networks
    J. R. Faeder, M. L. Blinov and W. S. Hlavacek
    Proceedings of ACM Symposium on Applied Computing, pp. 133-140, 2005.
  2. Rule-based modeling of biochemical networks
    J. R. Faeder, M. L. Blinov, B. Goldstein and W. S. Hlavacek
    Complexity, 10, 22-41, 2005.
  3. J. R. Faeder, M. L. Blinov, B. Goldstein, and W. S. Hlavacek
    Combinatorial complexity and dynamical restriction of network flows in signal transduction
    IEE Syst. Biol., 2, 5-15, 2005.
  4. Solvation dynamics in reverse micelles: The role of headgroup-solute interactions
    J. Faeder and B. M. Ladanyi
    J. Phys. Chem. B, 109, 6732-6740, 2005.
  5. ‘On-the-fly’ or ‘generate-first’ modeling?
    M. L. Blinov, J. R. Faeder, J. Yang, B. Goldstein, and W. S. Hlavacek.
    Nat. Biotechnol., 23, 1344-1345, 2005.


  1. Mathematical and computational models of immune-receptor signalling
    B. Goldstein, J. R. Faeder, and W. S. Hlavacek
    Nat. Rev. Immunol., 4, 445-456, 2004.
  2. BioNetGen: software for rule-based modeling of signal transduction based on the interactions of molecular domains
    M. L. Blinov, J. R. Faeder, B. Goldstein, and W. S. Hlavacek.
    Bioinformatics, 20, 3289-3292, 2004.


  1. Molecular dynamics simulations of the interior of aqueous reverse micelles.  II.  A comparison between sodium and potassium counterions
    J. Faeder, M. V. Albert, and B. M. Ladanyi
    Langmuir, 19, 2514-2520, 2003.
  2. Investigation of early events in FcεRI-mediated signaling using a detailed mathematical model
    J. R. Faeder, W. S. Hlavacek, I. Reischl, M. L. Blinov, H. Metzger, A. Redondo, C. Wofsy, and B. Goldstein
    J. Immunol., 170, 3769-3781, 2003.
  3. The complexity of complexes in signal transduction
    W. S. Hlavacek, J. R. Faeder, M. L. Blinov, A. S. Perelson, B. Goldstein
    Biotechnol. Bioeng. 84, 783-794, 2003.


  1. Modeling the early signaling events mediated by aggregation of FcεRI
    B. Goldstein, J. R. Faeder, W. S. Hlavacek, M. L. Blinov, A. Redondo, and C. Wofsy
    Mol. Immunol., 38, 1213-1219 (2002).


  1. Solvation dynamics in aqueous reverse micelles: A computer simulation study
    J. Faeder and B. M. Ladanyi
    J. Phys. Chem. B, 105, 11148-11158, 2001.
  2. Vibrational polarization beats in femtosecond CARS: A signature of dissociative pump-dump-pump wavepacket dynamics
    J. Faeder, I. Pinkas, G. Knopp, Y. Prior, and D. J. Tannor
    J. Chem. Phys., 115, 8440-8454, 2001.


  1. Molecular dynamics simulations of the interior of aqueous reverse micelles
    J. Faeder and B. M. Ladanyi
    J. Phys. Chem. B, 104, 1033-1046, 2000
  2. Charge flow and solvent dynamics in the photodissociation of solvated molecular ions
    R. Parson, J. Faeder, and N. Delaney
    J. Phys. Chem. A, 104, 9653-9665, 2000. (Feature Article)


  1. Photodissociation and recombination of solvated I2-: What causes the transient absorption peak?
    N. Delaney, J. Faeder, and R. Parson.
    J. Chem. Phys., 111, 452-455, 1999.
  2. Simulation of UV photodissociation of I2-·(CO2)n: Spin-orbit quenching via solvent mediated electron transfer
    N. Delaney, J. Faeder, and R. Parson
    J. Chem. Phys., 111, 651-663, 1999.
  3. Spin-orbit coupling in I·CO2 and I·OCS van der Waals complexes: beyond the pseudo-diatomic approximation
    A. Sanov, J. Faeder, R. Parson, and W. C. Lineberger
    Chem. Phys. Lett., 313, 812-819, 1999. (pdf)


  1. Ultrafast reaction dynamics in cluster ions: Simulation of the transient photoelectron spectrum of I2-Arn photodissociation
    J. Faeder and R. Parson
    J. Chem. Phys., 108, 3909-3914, 1998.
  2. Photodissociation of I2-·(OCS)n cluster ions: Structural implications
    S. Nandi, A. Sanov, N. Delaney, J. Faeder, R. Parson, and W. C. Lineberger
    J. Phys. Chem. A, 102, 8827-8835, 1998.
  3. An effective Hamiltonian for an electronically excited solute in a polarizable molecular solvent
    P. E. Maslen, J. Faeder, and R. Parson
    Mol. Phys., 94, 693-706, 1998.
  4. Modeling structure and dynamics of solvated molecular ions: Photodissociation and recombination in I2-·(CO2)n
    J. Faeder, N. Delaney, P. E. Maslen, and R. Parson
    Chem. Phys., 239, 525-547, 1998.
  5. The X2- files: Modeling photodissociation of molecular ions in clusters
    J. Faeder
    PhD thesis, University of Colorado at Boulder, 1998.
    (pdf) (GZippedPS)


  1. Charge flow and solvent dynamics in the photodissociation of cluster ions: A nonadiabatic molecular dynamics study of I2-·Arn
    J. Faeder, N. Delaney, P. Maslen, and R. Parson
    Chem. Phys. Lett., 270, 196-205, 1997.
  2. Photodissociation, recombination and electron transfer in cluster ions: A nonadiabatic molecular dynamics study of I2-(CO2)n
    N. Delaney, J. Faeder, P. E. Maslen, and R. Parson

    Oavsett de komplexa känslor impotens framkallar hos både kvinnor och män, är det bästa sättet att lugna känslorna, lugna rädslan och överväga dina alternativ för effektiv behandling – Bä Din medicinska miljö kanske inte erbjuder något betydande stöd för de psykologiska komponenterna av erektil dysfunktion.

    J. Phys. Chem. A, 101, 8147-8151, 1997.

  3. Ultrafast reaction dynamics in molecular cluster ions
    R. Parson and J. Faeder
    Science, 276, 1660, 1997.


  1. Ab initio calculations of the ground and excited states of I2- and ICl-
    P. E. Maslen, J. Faeder, and R. Parson
    Chem. Phys. Lett., 263, 63-72, 1996.


  1. Solvation of electronically excited I2
    P. E. Maslen, J. M. Papanikolas, J. Faeder, R. Parson, and S. V. ONeil
    J. Chem. Phys., 101, 5731, 1994.
  2. Time-resolved dynamics in large cluster ions
    W. C. Lineberger, M. Nadal, P. Campagnola, V. Vorsa, P. D. Kleiber, J. M. Papanikolas, P. E. Maslen, J. Faeder, R. Parson, and O. E. Poplawski
    Proceedings of the Robert A. Welch Foundation 38th Conference on Chemical Research: Chemical Dynamics of Transient Species, 1994.


  1. A distributed Gaussian approach to the vibrational dynamics of Ar-benzene
    J. Faeder
    J. Chem. Phys., 99, 7664, 1993.


  1. High resolution spectrum of the ν=1 Π state of ArHCN
    A. L. Cooksy, S. Drucker, J. Faeder, and W. Klemperer
    J. Chem. Phys., 95, 3017, 1991.

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