Patrick A. Fletcher
Laboratory of Biological Modeling
NIDDK, National Institutes of Health
Bethesda, MD 20892
E-mail: patrick.fletcher@nih.gov
Phone: (850) 980-5088
Education
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Ph.D, Mathematics (Biomathematics), August 2015. Florida State University, Tallahassee, Florida, USA. Dissertation title: Theoretical, Computational, and Experimental Topics in Anterior Pituitary Cell Signaling
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M.Sc, Mathematics (Mathematical Biology), November 2008. University of British Columbia, Vancouver, Canada. Thesis title: Modeling electrical spiking, bursting and calcium dynamics in gonadotropin releasing hormone (GnRH) secreting neurons
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B.S, Integrated Sciences (Mathematics and Biology), May 2005. University of British Columbia, Vancouver, Canada.
Publications
[1] P. A. Fletcher, B. Thompson, C. Liu, R. Bertram, L. S. Satin, and A. S. Sherman. Ca2+ release or ca2+ entry, that is the question: What governs ca2+ oscillations in pancreatic beta cells? American Journal of Physiology-Endocrinology and Metabolism, 2023. 10.1152/ajpendo.00030.2023.
[2] P. A. Fletcher and A. S. Sherman. Calcium signaling in context: case studies in endocrine cells. In Calcium Signals, 2053-2563, pages 10–1 to 10–14. IOP Publishing, 2023. 10.1088/978-0-7503-2009-2ch10.
[3] P. A. Fletcher, K. Smiljanic, R. M. Prévide, S. Constantin, A. S. Sherman, S. L. Coon, and S. S. Stojilkovic. The astroglial and stem cell functions of adult rat folliculostellate cells. Glia, 71(2):205–228, 2022. 10.1002/glia.24267.
[4] D. T. Asuzu*, R. Alvarez*, P. A. Fletcher*, D. Mandal, K. Johnson, W. Wu, A. Elkahloun, P. Clavijo, C. Allen, D. Maric, and others. Pituitary adenomas evade apoptosis via noxa deregulation in cushing’s disease. Cell reports, 40(8):111223, 2022. 10.1016/j.celrep.2022.111223.
[5] S. S. Stojilkovic, R. M. Previde, A. S. Sherman, and P. A. Fletcher. Pituitary corticotroph identity and receptor-mediated signaling: a transcriptomics perspective. Current Opinion in Endocrine and Metabolic Research, page 100364, 2022. 10.1016/j.coemr.2022.100364.
[6] P. A. Fletcher, I. Marinelli, R. Bertram, L. S. Satin, and A. Sherman. Pulsatile basal insulin secretion is driven by glycolytic oscillations. Physiology, 37(4):000–000, 2022. 10.1152/physiol.00044.2021.
[7] I. Marinelli, B. M. Thompson, V. S. Parekh, P. A. Fletcher, L. Gerardo-Giorda, A. S. Sherman, L. S. Satin, and R. Bertram. Oscillations in k (atp) conductance drive slow calcium oscillations in pancreatic β-cells. Biophysical Journal, 121(8):1449–1464, 2022. 10.1016/j.bpj.2022.03.015.
[8] I. Marinelli, V. Parekh, P. Fletcher, B. Thompson, J. Ren, X. Tang, T. L. Saunders, J. Ha, A. Sherman, R. Bertram, and others. Slow oscillations persist in pancreatic beta cells lacking phosphofructokinase m. Biophysical journal, 121(5):692–704, 2022. 10.1016/j.bpj.2022.01.027.
[9] M. Kucka, A. Gonzales-Iglesias, M. Tomic, R. M. Previde, K. Smiljanic, S. J. Sokanovic, P. A. Fletcher, A. Sherman, T. Balla, and S. S. Stojilkovic. Calcium-prolactin secretion coupling in rat pituitary lactotrophs is controlled by pi4-kinase alpha. Frontiers in Endocrinology, 12, 2021. 10.3389/fendo.2021.790441.
[10] P. A. Fletcher, R. M. Prévide, K. Smiljanic, A. Sherman, S. L. Coon, and S. S. Stojilkovic. Transcriptomic heterogeneity of sox2-expressing pituitary cells. BioRxiv, 2021. 10.1101/2021.12.10.472137.
[11] I. Marinelli, P. A. Fletcher, A. S. Sherman, L. S. Satin, and R. Bertram. Symbiosis of electrical and metabolic oscillations in pancreatic β-cells. Frontiers in Physiology, 12, 12 2021. 10.3389/fphys.2021.781581.
[12] J. C. Chang, P. Fletcher, J. Han, T. L. Chang, S. Vattikuti, B. Desmet, A. Zirikly, and C. C. Chow. Sparse encoding for more-interpretable feature-selecting representations in probabilistic matrix factorization. arXiv preprint arXiv:2012.04171, 2020. 10.48550/arXiv.2012.04171.
[13] K. Wang, K. Kretschmannova, R. M. Prévide, K. Smiljanic, Q. Chen, P. A. Fletcher, A. Sherman, and S. S. Stojilkovic. Cell-type-specific expression pattern of proton-sensing receptors and channels in pituitary gland. Biophysical Journal, 119(11):2335–2348, 2020. 10.1016/j.bpj.2020.10.013.
[14] M. M. Janjic, R. M. Prévide, P. A. Fletcher, A. Sherman, K. Smiljanic, D. Abebe, I. Bjelobaba, and S. S. Stojilkovic. Divergent expression patterns of pituitary gonadotropin subunit and gnrh receptor genes to continuous gnrh in vitro and in vivo. Scientific Reports, 9(1):1–14, 2019. 10.1038/s41598-019-56480-1.
[15] P. A. Fletcher, K. Smiljanic, R. Maso Prévide, J. Iben, T. Li, M. B. Rokic, A. Sherman, S. L. Coon, and S. S. Stojilkovic. Cell type-and sex-dependent transcriptome profiles of rat anterior pituitary cells. Frontiers in Endocrinology, 10, 2019. 10.3389/fendo.2019.00623.
[16] P. A. Fletcher, A. Sherman, and S. S. Stojilkovic. Common and diverse elements of ion channels and receptors underlying electrical activity in endocrine pituitary cells. Molecular and Cellular Endocrinology, 463:23–36, 2018. 10.1016/j.mce.2017.06.022.
[17] P. A. Fletcher, H. Zemkova, S. S. Stojilkovic, and A. Sherman. Modeling the diversity of spontaneous and agonist-induced electrical activity in anterior pituitary corticotrophs. Journal of Neurophysiology, 117(6):2298–2311, 2017. 10.1152/jn.00948.2016.
[18] P. A. Fletcher, R. Bertram, and J. Tabak. From global to local: exploring the relationship between parameters and behaviors in models of electrical excitability. Journal of Computational Neuroscience, 40(3):331–345, 2016. 10.1007/s10827-016-0600-1.
[19] A. E. Gonzalez-Iglesias, P. A. Fletcher, J. A. Arias-Cristancho, R. Cristancho-Gordo, C. V. Helena, R. Bertram, and J. Tabak. Direct stimulatory effects of oxytocin in female rat gonadotrophs and somatotrophs in vitro: Comparison with lactotrophs. Endocrinology, 156(2):600–612, 2015. 10.1210/en.2014-1543.
[20] P. A. Fletcher, F. Clément, A. Vidal, J. Tabak, and R. Bertram. Interpreting frequency responses to dose-conserved pulsatile input signals in simple cell signaling motifs. PLOS ONE, 9(4):1–10, 04 2014. 10.1371/journal.pone.0095613.
[21] M. N. Schulson, D. R. L. Scriven, P. A. Fletcher, and E. D. W. Moore. Couplons in rat atria form distinct subgroups defined by their molecular partners. Journal of Cell Science, 124(7):1167–1174, 2011. 10.1242/jcs.080929.
[22] P. A. Fletcher, D. R. Scriven, M. N. Schulson, and E. D. Moore. Multi-image colocalization and its statistical significance. Biophysical Journal, 99(6):1996 – 2005, 2010. 10.1016/j.bpj.2010.07.006.
[23] P. A. Fletcher and Y.-X. Li. An integrated model of electrical spiking, bursting, and calcium oscillations in gnrh neurons. Biophysical Journal, 96(11):4514 – 4524, 2009. 10.1016/j.bpj.2009.03.037.
[24] M. W. Richter, P. A. Fletcher, J. Liu, W. Tetzlaff, and A. J. Roskams. Lamina propria and olfactory bulb ensheathing cells exhibit differential integration and migration and promote differential axon sprouting in the lesioned spinal cord. Journal of Neuroscience, 25(46):10700–10711, 2005. 10.1523/JNEUROSCI.3632-05.2005.
* These authors contributed equally to the work.
Presentations
2022 |
Transcriptomic dynamics of the developing pineal gland at single cell resolution NICHD Neurosciences Affinity Group Seminar |
2022 |
Hypothesis: Pulsatile Basal Insulin Secretion is Driven by Glycolytic Oscillations 14th Annual Midwest Islet Club, Virtual Meeting |
2022 |
Sox2+ stem cells and astroglia in the postnatal pituitary Developmental Endocrinology, Metabolism, Genetics & Endocrine Oncology Research Conference, NICHD |
2020 |
The heterogeneity of Sox2-expressing cells in the pituitary gland at single-cell transcriptome resolution Developmental Endocrinology, Metabolism, Genetics & Endocrine Oncology Research Conference, NICHD |
2019 |
The dependence of glycolytic oscillations on calcium oscillations in models of pancreatic beta cells Society for Mathematical Biology Annual Meeting, Montreal Canada |
2017 |
Feature-Based Parameter Estimation in a Model of Anterior Pituitary Cell Electrical Activity SIAM Dynamical Systems, Snowbird UT |
2016 |
Modeling electrical activity in pituitary coriticotrophs. SIAM Life Sciences, Boston, MA |
2014 |
Real-Time Model calibration and prediction testing in pituitary cells using GPU and dynamic clamp. SIAM Life Sciences, Charlotte, NC |
2013 |
How do cells detect the frequency of pulsatile chemical signals? SIAM Dynamical Systems, Snowbird UT |
2012 |
Periodic forcing of simple models of cell signaling pathway components. FSU biomathematics seminar, Tallahassee, FL |
2011 |
Modeling frequency-dependent FSH transcription and secretion. Workshop in Mathematical Neuroendocrinology, INRIA, Paris, France |
Experience
Postdoctoral Fellowship
- 10/15–present:
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Laboratory of Biological Modeling, NIDDK, NIH. Supervisor: Arthur Sherman
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Analysis of single-cell RNA sequencing data from human and rat anterior pituitary cells, and rat pineal cells
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Modeling electrical activity and response to hormones in pituitary cells and pancreatic beta cells
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Statistical analysis video microscopy data from pancreatic islets
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Development of numerical simulation tools for parallel computation using graphics processing units (GPUs)
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Research Assistantships
- 01/11–08/15:
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Department of Mathematics, Florida State University. Supervisor: Richard Bertram
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Investigating the generation and decoding of pulsatile hormone patterns using mathematical models
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Performing calcium imaging experiments and mathematical modeling to study the response of pituitary cells to oxytocin
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Developing software for parallel numerical simulation of biophysical models of neuronal activity on graphics processing units (GPUs), for the purpose of rapid model calibration and studying how features of model solutions depend on model parameters
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- 02/12, 07/12:
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INRIA Rocquencourt, France. Supervisor: Frédérique Clément - Studied pulsatile forcing of non-linear systems inspired by intracellular signaling pathways
- 10/05–08/09:
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University of British Columbia.
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Department of Cellular and Physiological Sciences. Supervisor: Ed Moore - Quantified spatial patterning and its statistical significance in fluorescence microscopy images of signaling proteins involved in excitation-contraction coupling in cardiac myocytes.
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Department of Mathematics. Supervisor: Yue-Xian Li - Modeled electrical activities, calcium dynamics, and G-protein signaling of GnRH neurons and pituitary cells.
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Department of Mathematics. Supervisor: Eric Cytrynbaum - Compared a model of E. coli cell division machinery to experimental data.
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Department of Zoology. Supervisor: Jane Roskams - Quantified patterns of blood vessel growth and neurite outgrowth in fluorescence microscopy images of spinal cord explants.
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Teaching Assistantships
- 08/09–12/14:
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Florida State University, Department of Mathematics
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Lecturer. Courses taught: Calculus 1 and 3, Pre-calculus algebra, Biocalculus Laboratory
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Teaching assistant. Supervised computer laboratories in Pre-calculus algebra, and trigonometry
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- 09/06–05/08:
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University of British Columbia, Department of Mathematics - Tutoring, grading homework assignments
Awards
- 04/14:
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Distinguished Teaching Assistant award.
Languages and Programming Skills
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Bilingual: English, French
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Programming: MatLab, Python, C/C++, C#, OpenCL, CUDA, R, XPPAUT
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Course Delivery systems: Blackboard, WebAssign
Professional Service
Referee for papers submitted to Mathematical Biosciences, Journal of Theoretical Biology, PLOS Computational Biology, PLOS ONE, Journal of Neuroendocrinology, Computer Methods and Programs in Biomedicine.
Leadership
- 05/17:
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Co-organizer, Minisymposium for SIAM Dynamical Systems conference, titled State and Parameter Estimation in Models of Cellular Electrical Activity.
- 03/11–08/15:
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President, Vice-President, Treasurer, Kiteboarding Association at FSU. Responsible for activities of the club including organization of club trips, competitions and community service events, budget request presentations, purchasing and negotiation with industry contacts for kiteboard equipment, instruction of beginners, and repairing equipment.
- 01/11–04/11:
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Co-organizer of the Graduate Student Seminar, FSU Mathematics Department. Select, organize and schedule speakers and participants for the graduate student run seminar.
Career Goals
I aspire to continue my research in an academic setting, combining mathematical modeling along with statistical methods and data science to study endocrine physiology at cellular, tissue, and organism levels.
References
Available upon request.
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