Zobrazeno 1 - 10
of 36
pro vyhledávání: '"Joanna Tyrcha"'
Publikováno v:
BMC Bioinformatics, Vol 23, Iss 1, Pp 1-19 (2022)
Abstract Background The t-distributed Stochastic Neighbor Embedding (t-SNE) algorithm has emerged as one of the leading methods for visualising high-dimensional (HD) data in a wide variety of fields, especially for revealing cluster structure in HD s
Externí odkaz:
https://doaj.org/article/238e98ebae014a18833149d171579172
Publikováno v:
Entropy, Vol 16, Iss 3, Pp 1743-1755 (2014)
Transfer entropy is a frequently employed measure of conditional co-dependence in non-parametric analysis of Granger causality. In this paper, we derive analytical expressions for transfer entropy for the multivariate exponential, logistic, Pareto (t
Externí odkaz:
https://doaj.org/article/87796534ff464050bfa26fd1969cdd82
Autor:
John G Lock, Mehrdad Jafari Mamaghani, Hamdah Shafqat-Abbasi, Xiaowei Gong, Joanna Tyrcha, Staffan Strömblad
Publikováno v:
PLoS ONE, Vol 9, Iss 2, p e90593 (2014)
Heterogeneous and dynamic single cell migration behaviours arise from a complex multi-scale signalling network comprising both molecular components and macromolecular modules, among which cell-matrix adhesions and F-actin directly mediate migration.
Externí odkaz:
https://doaj.org/article/8242f4a16cd14b78a414665ea4073b58
Publikováno v:
Computational Management Science. 18:299-324
In this paper the concept of quantile-based optimal portfolio selection is introduced and a specific portfolio connected to it, the conditional value-of-return (CVoR) portfolio, is proposed. The CVoR is defined as the mean excess return or the condit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e9d195fc67267b3542b36091f42f46cf
https://doi.org/10.1007/s10287-021-00395-8
https://doi.org/10.1007/s10287-021-00395-8
Publikováno v:
Journal of Statistical Planning and Inference. 201:40-57
In this paper we derive the finite-sample distribution of the estimated weights of the tangency portfolio when both the population and the sample covariance matrices are singular. These results are ...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d052db23fe587b0da8e412acaa67eec5
https://doi.org/10.1016/j.jspi.2018.11.003
https://doi.org/10.1016/j.jspi.2018.11.003
The t-distributed Stochastic Neighbour Embedding (t-SNE) method has emerged as one of the leading methods for visualising High Dimensional (HD) data in a wide variety of fields, especially for revealing cluster structure in HD single cell transcripto
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3fd3796dce7970ff37e8778826dc9550
https://doi.org/10.21203/rs.3.rs-668207/v1
https://doi.org/10.21203/rs.3.rs-668207/v1
Realized covariance matrices are often constructed under the assumption that richness of intra-day return data is greater than the portfolio size, resulting in nonsingular matrix measures. However, when for example the portfolio size is large, assets
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c1a8a10599b28a7589add6541ebdaa48
https://hdl.handle.net/10419/244576
https://hdl.handle.net/10419/244576
We study a biological autoregulation process, involving a protein that enhances its own transcription, in a parameter region where bistability would be present in the absence of fluctuations. We calculate the rate of fluctuation-induced rare transiti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::920b17f802d2499617249f6c59dfc8d0
Autor:
Joanna Tyrcha
Publikováno v:
Mathematica Applicanda. 16
A transition probability model for sister cells is formalized. Assumptions are divided into three parts: assumptions based on empirical facts, general theoretical assumptions and detailed theoretical assumptions. The last group is considered in the b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::72b821f410fbe94eb1adefd3dec0602b
https://doi.org/10.14708/ma.v16i30.1697
https://doi.org/10.14708/ma.v16i30.1697
Autor:
Joanna Tyrcha, William B. Levy
Publikováno v:
Neurocomputing. :891-899
If there are many statistically independent excitatory inputs to a neuron, its net excitation is binomially distributed, and this distribution is well-approximated by a Gaussian because there are so many inputs. Because there are so many inputs, quan
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::09eb8b52fcaa0e766699776c47ccd116
https://doi.org/10.1016/j.neucom.2004.10.090
https://doi.org/10.1016/j.neucom.2004.10.090