Results 61 to 70 of about 7,762,001 (217)

ADP‐ribosylation: An emerging regulator of the epigenome

open access: yesMolecular Oncology, EarlyView.
ADP‐ribosylation has emerged as a dynamic epigenetic signaling mechanism that modifies histones and chromatin‐associated proteins. Through coordinated PARylation and MARylation, it integrates with other histone modifications to regulate chromatin structure, transcription factor activity, and gene expression, influencing genome function and disease ...
Cristel V. Camacho   +2 more
wiley   +1 more source

An M-estimator of multivariate tail dependence [PDF]

open access: yes, 2010
AN M-ESTIMATOR OF TAIL DEPENDENCE. Extreme value theory is the part of probability and statistics that provides the theoretical background for modeling events that almost never happen.
Krajina, A.   +2 more
core   +2 more sources

Some results on weak and strong tail dependence coefficients for means of copulas [PDF]

open access: yes
Copulas represent the dependence structure of multivariate distributions in a natural way. In order to generate new copulas from given ones, several proposals found its way into statistical literature.
Fischer, Matthias J., Klein, Ingo
core  

Castration‐resistant prostate cancer cells are addicted to the high activity of cyclin‐dependent kinase 2

open access: yesMolecular Oncology, EarlyView.
We show that emergence of castration‐resistant prostate (CRPC) is associated with significant upregulation of cyclins that positively regulate cyclin‐dependent kinase 2 (CDK2) and concomitant downregulation of CDK4 cyclins. This renders CRPC cells dependent on the high activity of CDK2, and CDK2 inhibitors synergistically sensitize CRPC cells to both ...
Joyeeta Chatterjee   +3 more
wiley   +1 more source

Arginine methylation as a regulatory ratchet in cancer: From substrate selection to malignant‐state stabilization

open access: yesMolecular Oncology, EarlyView.
Arginine methylation can be viewed as a persistence‐prone post‐translational modification regulated by a network of PRMTs. Competitive and compensatory interactions among PRMTs can redistribute methylation across substrate pools shaped by sequence, structural, spatial, and environmental layers, reinforcing RNA‐processing, chromatin, and signaling ...
So Hyun Kwon, Ji Min Lee
wiley   +1 more source

Tail Behavior of the Central European Stock Markets during the Financial Crisis [PDF]

open access: yes
In the paper we research statistical properties of the Central European stock markets. We focus mainly on the tail behavior of the Czech, Polish, and Hungarian stock markets and compare them to the benchmark U.S. and German stock markets. We fit the data
Jozef Baruník   +2 more
core   +2 more sources

Tail Behaviour of the Euro [PDF]

open access: yes
This paper empirically analyses risk in the Euro relative to other currencies. Comparisons are made between a sub period encompassing the final transitional stage to full monetary union with a sub period prior to this.
John Cotter
core   +2 more sources

A method of moments estimator of tail dependence [PDF]

open access: yes, 2007
In the world of multivariate extremes, estimation of the dependence structure still presents a challenge and an interesting problem. A procedure for the bivariate case is presented that opens the road to a similar way of handling the problem in a truly ...
Johan Segers   +10 more
core   +2 more sources

Regulation of the lncRNA NEAT1 by p53‐ΔNp63 crosstalk modulates the DNA damage response and therapeutic efficacy in HNSCC

open access: yesMolecular Oncology, EarlyView.
In head and neck squamous cell carcinoma (HNSCC) p53 and p63 exert opposite roles on the transcription regulation of the lncRNA NEAT1. Under basal conditions, p53 levels are low and p63 represses NEAT1 expression. Upon genotoxic stress, p53 is rapidly induced, displacing p63 from the NEAT1 promoter leading to NEAT1 transcriptional activation and ...
Sara De Domenico   +5 more
wiley   +1 more source

Heavy-tailed distributions in VaR calculations [PDF]

open access: yes
The essence of the Value-at-Risk (VaR) and Expected Shortfall (ES) computations is estimation of low quantiles in the portfolio return distributions.
Rafal Weron, Adam Misiorek
core  

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