Results 101 to 110 of about 1,253,621 (308)
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
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
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Molecular Oncology, EarlyView.Patient‐derived organoids (PDOs) from pancreatic, colorectal, and gastric cancers were used to evaluate standard and experimental therapies. Incorporating cancer‐associated fibroblasts (CAFs) into organoid cultures improved patient therapy outcome prediction.
Marcin Grochowski +12 more
wiley +1 more source
High-Dimensional Function Approximation with Neural Networks for Large Volumes of Data [PDF]
, 2018 Approximation of high-dimensional functions is a challenge for neural networks due to the curse of dimensionality. Often the data for which the approximated function is defined resides on a low-dimensional manifold and in principle the approximation of ...
core +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
Loss of proton‐sensing TDAG8 increases tumor progression in mouse models of colon cancer
Molecular Oncology, EarlyView.Loss of the pH‐sensing receptor TDAG8 accelerates colorectal cancer progression in mice. Animals lacking TDAG8 expression had increased tumor growth, DNA damage, and recruitment of tumor‐associated immune cells, including macrophages, neutrophils, and monocytes.
Ermanno Malagola +11 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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Molecular Oncology, EarlyView.Single‐cell multi‐omics reveals epigenetic heterogeneity across therapy‐adaptive tumor states, including quiescent/dormant, drug‐tolerant persister, and EMT‐like phenotypes. By linking regulatory features with state‐associated biomarkers, these approaches inform biomarker‐guided therapeutic strategies for evolving tumors.
Hee Jung Kim +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
Molecular Oncology, EarlyView.BCL9 and BCL9L drive bladder cancer progression by enhancing β‐catenin signaling, promoting proliferation, migration, invasion, and organoid growth. Genetic depletion of BCL9(L) suppresses malignant phenotypes, while pharmacological disruption of the β‐catenin/BCL9(L) complex with ZW4864 inhibits canonical Wnt signaling and tumor‐associated cellular ...
Roland Kotolloshi +11 more
wiley +1 more source