{"id":4,"date":"2014-12-17T19:03:29","date_gmt":"2014-12-17T19:03:29","guid":{"rendered":"http:\/\/csbweb.csb.pitt.edu\/Faculty\/Faeder\/?page_id=4"},"modified":"2019-05-27T17:46:41","modified_gmt":"2019-05-27T17:46:41","slug":"4-2","status":"publish","type":"page","link":"https:\/\/csbweb.csb.pitt.edu\/Faculty\/Faeder\/","title":{"rendered":"Home"},"content":{"rendered":"

\"\"My lab is interested in developing mathematical models of biological regulatory processes that integrate specific knowledge about protein-protein interactions. We develop and maintain a simulation framework called BioNetGen<\/a> that allows rule-based specification of biochemical reaction networks and provides both deterministic and stochastic modeling capabilities. Current research includes the development of specific models of signal transduction and the development of new stochastic simulation algorithms that will greatly broaden the scope of models that can be developed. Other research areas include model reduction, parameter estimation and uncertainty analysis, and automated model construction from databases of protein interactions.<\/p>\n

I am also the Pitt co-director of the Joint Carnegie Mellon – University of Pittsburgh PhD Program in Computational Biology<\/a>.<\/p>\n

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Full bibliography on ORCiID<\/a><\/p>\n

Recent Papers:<\/strong><\/p>\n

J. J. Tapia, \u00a0A. S. Saglam, J. Czech, R. Kuczewski, T. M. Bartol, T. J. Sejnowski, and J. R. Faeder\u00a0(2019)\u00a0\u201cMCell-R: A Particle-Resolution Network-Free Spatial Modeling Framework,\u201d Methods in Molecular Biology<\/em>, 1945<\/b>, 203\u2013229.\u00a0doi:10.1007\/978-1-4939-9102-0_9<\/a>. (arxiv preprint<\/a>)<\/p>\n

Gupta, S, \u00a0et al. (2018) Spatial Stochastic Modeling with MCell and CellBlender. In\u00a0Quantitative Biology: Theory, Computational Methods and Examples of Models<\/em>, B. Munsky, W. Hlavacek, and L. Tsimring, Eds. MIT Press, ISBN:9780262038089<\/a>. (arxiv<\/a>)<\/p>\n

Sekar, JAP, and Faeder, JR (2018) An Introduction to Rule-based Modeling of Immune Receptor Signaling. In Systems Immunology: An Introduction to Modeling Methods for Scientists<\/em>, J. Das and C. Jayaprakash, Eds. Taylor and Francis, ISBN: 978-1498717403. (arxiv<\/a>)<\/p>\n

Kaya, C, Cheng, MH, Block, ER, Sejnowski, TJ, Sorkin, A , Faeder, JR, and Bahar, I (2018) \u201cSignificance of Neuronal Structural Complexity and Spatial Heterogeneity in Modulating Dopamine Reuptake Dynamics,\u201d eNeuro<\/em>, doi:10.1523\/ENEURO.0298-17.2017<\/a>.<\/p>\n

Gupta, S, Hainsworth, L, Hogg, JS, Lee, REC, and Faeder, JR (2018)\u00a0\u201cEvaluation of Parallel Tempering to Accelerate Bayesian Parameter Estimation in Systems Biology,\u201d\u00a0Proceedings of PDP 2018<\/a>,<\/em>\u00a0doi:10.1109\/PDP2018.2018.00114<\/a>. (arxiv<\/a>)<\/p>\n

Sekar, JAP, \u00a0Tapia JJ, and Faeder JR (2017) \u201cAutomated Visualization of Rule-based Models,\u201d\u00a0PLOS Computational Biology<\/em>,\u00a0doi:10.1371\/journal.pcbi.1005857<\/a>.<\/p>\n

Zhang, Q, Gupta, S, Schipper, DL, Kowalczyk, GJ, Faeder, JR, and Lee, REC. (2017) \u201cDose discrimination in single cells,\u201d Cell Systems<\/em>, doi:10.1016\/j.cels.2017.10.011<\/a>.<\/p>\n

Sekar JAP, Hogg, JS, and Faeder JR (2017) Energy-based Modeling in BioNetGen. Proceedings – 2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016 (link<\/a>)<\/p>\n

Harris, LA, et al. \u00a0(2016) BioNetGen 2.2: Advances in Rule-Based Modeling. Bioinformatics<\/em>,\u00a0<\/em>32<\/strong>,\u00a0<\/em>3366\u20133368 .<\/em>\u00a0doi:10.1093\/bioinformatics\/btw469<\/a>.<\/p>\n

Donovan, RM et al. (2016)\u00a0Unbiased Rare Event Sampling in Spatial Stochastic Systems Biology Models Using a Weighted Ensemble of Trajectories.\u00a0PLOS Computational Biology<\/i> 12<\/strong>,\u00a0<\/strong>e1004611. doi:10.1371\/journal.pcbi.1004611.\u00a0[In collaboration with D. M. Zuckerman]\u00a0\u00a0(link<\/a>)
\n<\/b><\/p>\n

Hawse, WF, et al. (2015) Cutting Edge: Differential regulation of PTEN by TCR, Akt and FoxO1 controls CD4+ T cell fate\u00a0 decisions. J. Immunol.,<\/i>\u00a0doi:10.4049\/jimmunol.1402554.<\/span> [In collaboration with P. A. Morel]\u00a0(link<\/a>) <\/p>\n","protected":false},"excerpt":{"rendered":"

My lab is interested in developing mathematical models of biological regulatory processes that integrate specific knowledge about protein-protein interactions. We develop and maintain a simulation framework called BioNetGen that allows rule-based specification of biochemical reaction networks and provides both deterministic and stochastic modeling capabilities. Current research includes the development of …<\/p>\n

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