activity
20062020
most citedElucidating distinct ion channel populations on the surface of hippocampal neurons via single-particle tracking recurrence analysis

43 citations · 49 across the 2 of their papers we have counts for

collaborators

5 papers

cond-mat.stat-mech2020

Leveraging large-deviation statistics to decipher the stochastic properties of measured trajectories

Samudrajit Thapa, Agnieszka Wyłomańska, Grzegorz Sikora +5

Extensive time-series encoding the position of particles such as viruses, vesicles, or individual proteins are routinely garnered in single-particle tracking experiments or superco…

math.PR2018

Large deviations of time-averaged statistics for Gaussian processes

J. Gajda, A. Wylomanska, H. Kantz +2

In this paper we study the large deviations of time averaged mean square displacement (TAMSD) for Gaussian processes. The theory of large deviations is related to the exponential d…

cond-mat.stat-mech2018

Probabilistic properties of detrended fluctuation analysis for Gaussian processes

G. Sikora, M. Hoell, A. Wylomanska +3

The detrended fluctuation analysis (DFA) is one of the most widely used tools for the detection of long-range correlations in time series. Although DFA has found many interesting a…

physics.bio-ph201743 cited

Elucidating distinct ion channel populations on the surface of hippocampal neurons via single-particle tracking recurrence analysis

Grzegorz Sikora, Agnieszka Wyłomańska, Janusz Gajda +4

Protein and lipid nanodomains are prevalent on the surface of mammalian cells. In particular, it has been recently recognized that ion channels assemble into surface nanoclusters i…

physics.data-an20066 cited

The dependence structure for PARMA models with alpha-stable innovations

Joanna Nowicka-Zagrajek, Agnieszka Wylomanska

In this paper we investigate the dependence structure for PARMA models (i.e. ARMA models with periodic coefficients) with symmetric alpha-stable innovations. In this case the covar…