Stockholm university

Joanna Tyrcha

About me

I am a professor in mathematical statistics and the head of the Department of Mathematics at Stockholm University.

Education

- M.S., Mathematical Statistics, Warsaw School of Economics, Poland, 1980
- Ph.D. in Mathematics, Jagiellonian University, Cracow, Poland, 1989
- Associate professor (docent), Mathematical Statistics, Stockholm University, 2003
- Professor, Mathematical Statistics, Stockholm University, 2011

Employment

  • 1980-1989 Assistant, Institute of Computer Science, Polish Academy of Sciences, Warsaw,  Poland
  • 1990 Postdoctoral position, McGill University, The Centre for Nonlinear Dynamics in Physiology and Medicine, Montréal, Canada
  • 1989-1992 Assistant professor, Institute of Computer Science, Polish Academy of Sciences, Warsaw,  Poland
  • 1992-1994 Fellowship, Dept. of Numerical Analysis and Computer Science, Royal Institute of Technology, Stockholm, Sweden
  • 1994-1996 Parental leave
  • 1996-1998 Temporary lecturer, Dept. of Mathematics, Royal Institute of Technology; Dept. of Mathematics, Stockholm University; Dept. of Mathematics, Uppsala University, Sweden
  • 1998-... Lecturer in mathematical statistics, Dept. of Mathematics, Stockholm University, Sweden
  • 2008-2010 Director of undergraduate studies, Division of Mathematical Statistics, Dept. of Mathematics, Stockholm University
  • 2011-2017 Head of Division of Mathematical Statistics, Dept. of Mathematics, Stockholm University
  • 2018-... Head of Deapartment of Mathematics, Stockholm University

 

Teaching

Academic year 2015/2016

- Probability Theory, 7.5 ECTS, September-October 2015

- Econometrics, 7.5 ECTS, March-May 2016

Research

My research areas are statistical inference, econometrics, neuroscience, and bio-mathematics. In particular, my interests lie in: models of cell cycle, connectivity in neural networks, biological information processing, causality problems, and ion channels models.

Publications

Peer-reviewed articles

1. Tyrcha, J. [1987] Transition Probability Model in the cell cycle.
Applied Mathematics 3, 49-61.


2. Tyrcha J. [1988]
Asymptotic stability in a generalized probabilistic/deterministic model of the cell cycle. J. Math. Biol. 26, 465-475.


3. Kowalczyk T. and Tyrcha J. [1989]
Multivariate gamma distributions - properties and shape estimation.
Statistics 20, 465-474.

4. Komorowski T. and
Tyrcha J. [1989]
Asymptotic properties of some Markov operators. Bull. PAS Math. Vol.36., No. 11-12.


5. Lasota A. and Tyrcha J. [1991]
On the strong convergence to equilibrium for randomly perturbed dynamical systems. Ann. Polon. Math. L.III.1, 79-89.

6. Lasota A., Mackey M.C. and Tyrcha J. [1992]
The statistical dynamics of irregular biological events. J. Math. Biol. 30, 775-800.

7. Mielniczuk J. and Tyrcha J. [1993]
Consistency of multilayer perceptron regression estimators. Neural Networks, Vol. 6, pp. 1019-1022.

8. Wu, X. B., Tyrcha, J. M. and Levy, W. B. [1997]
A special role for input codes in solving  the transverse patterning problem. Computational Neuroscience: Trends in Research, ed. J. M. Bower  (New York: Plenum Press), 885-889.

9. Wu X., Tyrcha J. and Levy W.B. [1998]
A Neural Network Solution to the Transverse Patterning Problem Depends on Repetition in the Input Code. Biol. Cybern. 79, 203-213.


10. Tyrcha J., Sundberg R., Lindskog P. and Sundström B.[2000]
Statistical modelling and saddle point approximation of tail probabilities for accumulated  splice loss in fibre optic networks. J. Applied Statistics, Vol. 27, No. 2, 245-256.

11.
Tyrcha J. [2001]
Age-dependent cell cycle models. J. theor. Biol. 213, 89-101.

12.
Tyrcha J. [2004]
Cell cycle progression. Comptes Rendus. Biologies 327, 193-200.

13. 
Tyrcha, J. & Levy, W.B. [2004]
Another contribution by synaptic failures to energy efficient processing by neurons. Neurocomputing 58-60, 59-66.

14. 
Tyrcha, J. & Levy, W. B. [2005]
Synaptic failures and a Gaussian excitation distribution. Neurocomputing 65-66C, 891-899.

15. 
Tyrcha J. [2007]
Dynamics of integrate and fire models. In: "Mathematical Modeling of Biological Systems", Volume II. A. Deutch, R. Bravo de la Parra, R. de Boer, O. Diekmann, P. Jagers, E. Kisdi, M. Kretzschmar, P. Lansky and H. Metz (eds). Birkäuser, Boston, 235-246.

16.  Nellåker C., Uhrzander F.,
Tyrcha J. and Karlsson H. [2008]
Mixture models for analysis of melting temperature data. BMC Bioinformatics 9:370.

17.  Roudi  Y.,
Tyrcha J. and  Hertz J. [2009]
Ising Model for Neural Data: Model Quality and Approximate Methods for Extracting Functional Connectivity. Physical Review E (Vol.79, No.5):

18.  Nellåker C., Li F., Uhrzander F.,
Tyrcha J. and Karlsson H. [2009]
Expression profiling of repetitive elements by melting temperature anlysis: variation in HERV-W gag expression across human individuals and tissues. BMC Genomics 10:532

19. Hertz J., Roudi Y.,
Tyrcha J. [2013] Book chapter
Ising model for inferring network structure from spike data in “Principle of Neural Coding” edited by S. Panzeri and R. Q. Quiroga.
http://arxiv.org/abs/1106.1752

20. Tyrcha J., Roudi Y., Marsili M. and Hertz J. [2013]
Effect of Nonstationarity on Models Inferred from Neural Data. Journal of Statistical Mechanics: Theory and Experiment, Vol 2013, March 2013.


21. Tyrcha J. and Hertz J. [2014]
Network inference with hidden units. Mathematical Biosciences and Engineering vol 11, no.1, 149-165.

22. Jafari-Mamghani M., Lock JG., Shafqat-Abbasi H., Gong X., Tyrcha J., and Strömblad S. [2014]
Plasticity in the Macromolecular-Scale Caused Networks of Cell Migration. PLoS ONE 9(2): e90593.

23. Jafari-Mamghani M. and Tyrcha J. [2014]
Tansfer entropy expressions for a class of non-Gaussian distributions. Entropy 2014, 16(3) 1743-1755.

24. Battistin, C., Hertz, J., Tyrcha, J. & Roudi Y. [2015]
Belief propagation and replicas for inference and learning in a kinetic Ising model with hidden spins. Journal of Statistical Mechanics: Theory and Experiment, Volume 2015, May 2015.

Peer-reviewed conference contributions:

1. Tyrcha J. [1987]
On estimation of parameters of gamma distributions. Proceedings of the Conference "Statistical Data Analysis", Varna, Bulgaria, September 1987.

2.
Tyrcha J. [1989]
Asymptotic stability of the cell cycle models in the case of the exponential and linear growth. Proceedings of the Conference ”Stochastic methods in experimental sciences”, COSMEX-89, Szklarska Poreba, Poland, September 1989.

3.
Tyrcha J. [1990]
Stability problems for dynamical systems with stochastic perturbations. Proceedings of the Meeting Matematische Modelle in der Biologie, Oberwolfach, Germany, February 1990.

4.
Tyrcha J. [1991]
Applications of perturbed dynamical systems to cell cycle modelling. Math Biosci. 1991 Nov, 107(2), 149-555. Spread of Epidemics: stochastic modeling and data analysis. Proceedings of a research workshop. Skokloster, Balsta, Sweden, August 8-12, 1990.

5. Wu X.,
Tyrcha J. and Levy W.B. [1996]
Role for Input Codes in Solving A Special the Tranverse Patterning Problem. CNS*96 (Conference on Computational Neuroscience)

6. Levy W.B., Wu X. and
Tyrcha J. [1996]
Solving the Tranverse Patterning Problem by Learning Context. INNS World Congress on Neural Networks, 1305-1309.

7.
Tyrcha J. and Hertz J. [2007]
Spike statistics in a High_conductance Cortical Network Model. Proceedings of 5th Nordic Neuroinformatics Workshop, Espoo, Finland, October 2007.

8.
Tyrcha J. and Hertz J. [2008]
Spike pattern distributions in model cortical networks. Proceedings of Computational and Systems Neuroscience 2008 (COSYNE-2008). Salt Lake City, Utah, USA.

9.
Tyrcha J. and Hertz J. [2008]
Testing Algorithms for Extracting Functional Connectivity from Spike Data. Proceedings of 1st INCF Congress of Neuroinformatics, Stockholm, 2008.

10. Roudi Y.,
Tyrcha J. and Hertz J. [2009]
Fast and reliable methods for extracting functional connectivity in large populations. BMC Neuroscience, 10, Suppl.1.

11. Hertz J., Roudi Y., Thorning A.,
Tyrcha J., Aurell E., Zeng H. [2010]
Inferring network connectivity using kinetic Ising models. BMC Neuroscience 2010, 11(Suppl 1):P51

12.
Tyrcha J., Roudi Y. and Hertz J. [2011]
Network inference from non-stationary spike trains, BMC Neuroscience, 12 (Suppl 1):P150.

Compendium

Andersson P. and Tyrcha J. [2010]
Econometrics. Stockholm universitet.

Books

1. Cwik J., Niewiadomska-Bugaj M., Pleszczynska E., and Tyrcha J. [1986]
Statistical inference schemes in archeological exploring. In Theory and practice of archeological exploring. Editors: Hansel W., Donato G. and Tabaczynski S. Vol.1. Methodological premises, 305-328, Ossolineum (in Polish).

2. Cwik J., Niewiadomska-Bugaj M., Pleszczynska E., and Tyrcha J. [1986]
Schemi di inferenza statistica nelle ricerche archeologiche. In Theoria e practica della ricerca archeologica. Editors: Hansel W., Donato G. and Tabaczynski S. Vol.1. Premesse metodologiche, 325-351, Quadrante Edizioni (in Italian).

Reports

1.  Wisniewska, J., Tyrcha J. [1982]
Generation of random numbers. ICS PAS REPORTS 473, Warsaw (in Polish).

2. Tyrcha, J. [1984]
Knowledge representation system in medical diagnosis. ICS PAS REPORTS 541, Warsaw.

3. Tyrcha J., Sundberg R., Lindskog P. and Sundström B.[1998]
Statistical modelling and saddle point approximation of tail probabilities for accumulated splice loss in fibre optics. Report No. B:45, December 1998.

4. Tyrcha J. [2000]
Asymptotic Stability of the Mass Distribution in the Case of the Linear and Exponential Growth in Probabilistic Models of the Cell Cycle. Research Report 2000:2, ISSN 0282-9150.