Results 111 to 120 of about 4,092,880 (310)
Independence Test for High Dimensional Random Vectors [PDF]
This paper proposes a new mutual independence test for a large number of high dimensional random vectors. The test statistic is based on the characteristic function of the empirical spectral distribution of the sample covariance matrix.
G. Pan, J. Gao, Y. Yang, M. Guo
core
Molecular Oncology, EarlyView.We identify USP29 as the only DUB mirroring CA9 expression, a marker of hypoxia and HIF pathway activation associated with PCA aggressiveness. USP29 stabilizes HIF‐1α and HIF‐2α via a noncanonical mechanism that is independent of PHD/pVHL activity yet relies on proteasomal regulation, establishing USP29 as a previously unrecognized regulator of hypoxic
Amelie S Schober +16 more
wiley +1 more source
Design of high dimensional data acquisition system of industrial field
Gong-kuang zidonghua, 2013 For problem of high-speed data acquisition and transmission of high dimensional spectral data of industrial field, the paper proposed a design scheme of high dimensional data acquisition system. The system selects TMS320C6713B DSP chip as core processing
ZHAO An-xin, ZHANG Cai-tian
doaj +1 more source
Molecular Oncology, EarlyView.The novel styrylquinazolinone‐based molecule W1B effectively suppresses glioblastoma by inhibiting IGF1R and EGFR. In high‐glucose microenvironments driving tumor resistance, W1B acts synergistically with the EGFR inhibitor dacomitinib. This combination safely blocks compensatory survival signaling in zebrafish xenograft models. Showcasing promising in
Patryk Rurka +9 more
wiley +1 more source
Inference for high-dimensional sparse econometric models [PDF]
This article is about estimation and inference methods for high dimensional sparse (HDS) regression models in econometrics. High dimensional sparse models arise in situations where many regressors (or series terms) are available and the regression ...
Christian Hansen +2 more
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High-dimensional statistical learning: Roots, justifications, and potential machineries [PDF]
, 2016 High-dimensional data generally refer to data in which the number of variables is larger than the sample size. Analyzing such datasets poses great challenges for classical statistical learning because the finite-sample performance of methods developed ...
Zollanvari, Amin, Amin Zollanvari
core +1 more source
Replication Data for: Strain propagation in layered two-dimensional halide perovskites
, 2022 Replication Data for: Strain propagation in layered two-dimensional halide perovskites published in Science ...
Fu, Jianhui
core +1 more source
Liquid biopsy‐based diagnostic evaluation of hypermethylated CpG sites for ovarian cancer diagnosis
Molecular Oncology, EarlyView.This schematic outlines the workflow from biomarker identification to duplex MethyLight assay validation for epithelial ovarian cancer diagnosis using cfDNA‐based liquid biopsy. Initial screening of hypermethylated CpG candidates (cg02957270, cg10061138 cg00480298, COL2A1) was performed in tissue using ARMS‐PCR, COBRA, qPCR and image analysis. Selected
Deepa Bisht +3 more
wiley +1 more source
Analyzing high dimensional correlated data using feature ranking and classifiers
Computational and Mathematical Biophysics, 2019 The Illumina Infinium HumanMethylation27 (Illumina 27K) BeadChip assay is a relatively recent high-throughput technology that allows over 27,000 CpGs to be assayed.
Patil Abhijeet R +3 more
doaj +1 more source
KERNEL LOGISTIC REGRESSION-LINEAR FOR LEUKEMIA CLASSIFICATION USING HIGH DIMENSIONAL DATA
JUTI: Jurnal Ilmiah Teknologi Informasi, 2009 Kernel Logistic Regression (KLR) is one of the statistical models that has been proposed for classification in the machine learning and data mining communities, and also one of the effective methodologies in the kernel–machine techniques.
S P Rahayu +3 more
doaj +1 more source