Results 81 to 90 of about 3,880,374 (297)

Robust Estimation of High-Dimensional Mean Regression [PDF]

open access: yes, 2014
Data subject to heavy-tailed errors are commonly encountered in various scientific fields, especially in the modern era with explosion of massive data.
Fan, Jianqing, Li, Quefeng, Wang, Yuyan
core  

Structural instability impairs function of the UDP‐xylose synthase 1 Ile181Asn variant associated with short‐stature genetic syndrome in humans

open access: yesFEBS Letters, EarlyView.
The Ile181Asn variant of human UDP‐xylose synthase (hUXS1), associated with a short‐stature genetic syndrome, has previously been reported as inactive. Our findings demonstrate that Ile181Asn‐hUXS1 retains catalytic activity similar to the wild‐type but exhibits reduced stability, a looser oligomeric state, and an increased tendency to precipitate ...
Tuo Li   +2 more
wiley   +1 more source

Rate optimal multiple testing procedure in high-dimensional regression

open access: yes, 2014
Multiple testing and variable selection have gained much attention in statistical theory and methodology research. They are dealing with the same problem of identifying the important variables among many (Jin, 2012).
Ji, Pengsheng, Zhao, Zhigen
core  

PARP inhibitors elicit distinct transcriptional programs in homologous recombination competent castration‐resistant prostate cancer

open access: yesMolecular Oncology, EarlyView.
PARP inhibitors are used to treat a small subset of prostate cancer patients. These studies reveal that PARP1 activity and expression are different between European American and African American prostate cancer tissue samples. Additionally, different PARP inhibitors cause unique and overlapping transcriptional changes, notably, p53 pathway upregulation.
Moriah L. Cunningham   +21 more
wiley   +1 more source

False Variable Selection Rates in Regression

open access: yes, 2013
14 figures, 21 pages.
G'Sell, Max Grazier   +2 more
openaire   +2 more sources

Adenosine‐to‐inosine editing of miR‐200b‐3p is associated with the progression of high‐grade serous ovarian cancer

open access: yesMolecular Oncology, EarlyView.
A‐to‐I editing of miRNAs, particularly miR‐200b‐3p, contributes to HGSOC progression by enhancing cancer cell proliferation, migration and 3D growth. The edited form is linked to poorer patient survival and the identification of novel molecular targets.
Magdalena Niemira   +14 more
wiley   +1 more source

Adaptive testing on a regression function at a point

open access: yes, 2015
We consider the problem of inference on a regression function at a point when the entire function satisfies a sign or shape restriction under the null. We propose a test that achieves the optimal minimax rate adaptively over a range of H\"{o}lder classes,
Armstrong, Timothy
core   +1 more source

Emerging role of ARHGAP29 in melanoma cell phenotype switching

open access: yesMolecular Oncology, EarlyView.
This study gives first insights into the role of ARHGAP29 in malignant melanoma. ARHGAP29 was revealed to be connected to tumor cell plasticity, promoting a mesenchymal‐like, invasive phenotype and driving tumor progression. Further, it modulates cell spreading by influencing RhoA/ROCK signaling and affects SMAD2 activity. Rho GTPase‐activating protein
Beatrice Charlotte Tröster   +3 more
wiley   +1 more source

Exchange Rate, Gold Price, and Stock Market Nexus: A Quantile Regression Approach

open access: yesRisks, 2020
In this study, we examine an empirical relationship between stock market volatility with the exchange rate and gold prices of an emerging market, “Pakistan”, employing daily and monthly data (PSX-100 Index) covering from 2001: Q3 to 2018: Q2.
Rizwan Ali   +5 more
doaj   +1 more source

Optimal Rates of Distributed Regression with Imperfect Kernels

open access: yes, 2020
Distributed machine learning systems have been receiving increasing attentions for their efficiency to process large scale data. Many distributed frameworks have been proposed for different machine learning tasks. In this paper, we study the distributed kernel regression via the divide and conquer approach.
Sun, Hongwei, Wu, Qiang
openaire   +3 more sources

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