Results 61 to 70 of about 919,275 (319)
Hybrid modeling and prediction of oyster norovirus outbreaks
Journal of Water and Health, 2021 This paper presents a hybrid model for predicting oyster norovirus outbreaks by combining the Artificial Neural Networks (ANNs) and Principal Component Analysis (PCA) methods and using the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite ...
Shima Shamkhali Chenar, Zhiqiang Deng
doaj +1 more source
Aggressive prostate cancer is associated with pericyte dysfunction
Molecular Oncology, EarlyView.Tumor‐produced TGF‐β drives pericyte dysfunction in prostate cancer. This dysfunction is characterized by downregulation of some canonical pericyte markers (i.e., DES, CSPG4, and ACTA2) while maintaining the expression of others (i.e., PDGFRB, NOTCH3, and RGS5).
Anabel Martinez‐Romero +11 more
wiley +1 more source
Development and Evaluation of an Electronic Nose System Based on MOS Sensors to Detect and to Distinguish Lemon Essential Oils [PDF]
Journal of Agricultural Machinery, 2019 Introduction Essences or essential oils are aromatic compounds that are found in different organs of the plants. Essences can be classified into three groups of natural, synthetic and natural like.
P Fayyaz +3 more
doaj +1 more source
Statistical Shape Analysis using Kernel PCA [PDF]
, 2006 ©2006 SPIE--The International Society for Optical Engineering. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or ...
AD Roy +17 more
core +3 more sources
Molecular Oncology, EarlyView.ERRFI1, a neural crest (NC)‐associated gene, was upregulated in melanoma and negatively correlated with the expression of melanocytic differentiation markers and the susceptibility of melanoma cells toward BRAF inhibitors (BRAFi). Knocking down ERRFI1 significantly increased the sensitivity of melanoma cells to BRAFi.
Nina Wang +8 more
wiley +1 more source
Information-theoretically Optimal Sparse PCA
, 2014 Sparse Principal Component Analysis (PCA) is a dimensionality reduction technique wherein one seeks a low-rank representation of a data matrix with additional sparsity constraints on the obtained representation. We consider two probabilistic formulations
Deshpande, Yash, Montanari, Andrea
core +1 more source
Molecular Oncology, EarlyView.HDAC4 is degraded by the E3 ligase FBXW7. In colorectal cancer, FBXW7 mutations prevent HDAC4 degradation, leading to oxaliplatin resistance. Forced degradation of HDAC4 using a PROTAC compound restores drug sensitivity by resetting the super‐enhancer landscape, reprogramming the epigenetic state of FBXW7‐mutated cells to resemble oxaliplatin ...
Vanessa Tolotto +13 more
wiley +1 more source
Arab Journal of Forensic Sciences & Forensic MedicineThe study employed Thin Layer Chromatography (TLC) and Attenuated Total Reflectance-Fourier Transform Infrared (ATR-FTIR) to analyze local brands of vermillion and lipstick samples.
Aishwarya P. V +4 more
doaj +1 more source
Semi-Supervised Kernel PCA [PDF]
, 2010 We present three generalisations of Kernel Principal Components Analysis (KPCA) which incorporate knowledge of the class labels of a subset of the data points.
Christian Walder +4 more
core +2 more sources
Phase Transitions in Sparse PCA
, 2015 We study optimal estimation for sparse principal component analysis when the number of non-zero elements is small but on the same order as the dimension of the data. We employ approximate message passing (AMP) algorithm and its state evolution to analyze
Krzakala, Florent +2 more
core +2 more sources