Results 121 to 130 of about 2,126,918 (327)

Potential Errors in the Application of Principal Component (Eigenvector) Analysis to Geophysical Data [PDF]

, 1982
Thomas R. Karl, Albert J. Koscielny, Henry F. Díaz   +2 more
openalex   +1 more source

Transcriptome‐wide analysis of circRNA and RBP profiles and their molecular relevance for GBM

Molecular Oncology, EarlyView.
CircRNAs are differentially expressed in glioblastoma primary tumors and might serve as therapeutic targets and diagnostic markers. The investigation of circRNA and RNA‐binding proteins (RBPs) interactions shows that distinct RBPs play a role in circRNA biogenesis and function.
Julia Latowska‐Łysiak, Żaneta Zarębska, Marcin P. Sajek, Adriana Grabowska, Alessia Buratin, Paweł Głodowicz, Julia O. Misiorek, Konrad Kuczyński, Stefania Bortoluzzi, Marek Żywicki, Jan G. Kosiński, Agnieszka Rybak‐Wolf, Rafał Piestrzeniewicz, Anna M. Barciszewska, Katarzyna Rolle   +14 more
wiley   +1 more source

Demonstrating the Mechanics of Principal Component Analysis via Spreadsheets

Spreadsheets in Education, 2019
Principal component analysis (PCA) is a popular multivariate statistical method that is used for dimensionality reduction. When teaching PCA in a marketing research or business analytics course, the mechanics of the analysis are often not communicated to
Michael Brusco
doaj  

Highly multiplexed digital PCR assay for simultaneous quantification of variant allele frequencies and copy number alterations of KRAS and GNAS in pancreatic cancer precursors

Molecular Oncology, EarlyView.
Combining melting curve analysis enhances the multiplexing capability of digital PCR. Here, we developed a 14‐plex assay to simultaneously measure single nucleotide mutations and amplifications of KRAS and GNAS, which are common driver genes in pancreatic cancer precursors. This assay accurately quantified variant allele frequencies in clinical samples
Junko Tanaka, Tatsuo Nakagawa, Yusuke Ono, Yoshio Kamura, Takeshi Ishida, Hidemasa Kawabata, Kenji Takahashi, Hiroki Sato, Andrew S. Liss, Yusuke Mizukami, Takahide Yokoi   +10 more
wiley   +1 more source

THE GENERALIZED METHOD FOR PRINCIPAL COMPONENTS OF SCALE ANALYSIS

, 1965
Sukeyori Shiba
openalex   +2 more sources

Exploration of heterogeneity and recurrence signatures in hepatocellular carcinoma

Molecular Oncology, EarlyView.
This study leveraged public datasets and integrative bioinformatic analysis to dissect malignant cell heterogeneity between relapsed and primary HCC, focusing on intercellular communication, differentiation status, metabolic activity, and transcriptomic profiles.
Wen‐Jing Wu, Jianchao Wang, Fuqing Chen, Xuefeng Wang, Bin Lan, Ruyi Fu, Hong Wen, Fangfang Chen, Wei Hong, Tian‐Yu Tang, Ying He, Gang Chen, Jianyin Zhou, Hai‐Long Piao, Di Chen, Shu‐Yong Lin   +15 more
wiley   +1 more source

CLASSIFICATION OF MAIZE LINES COLLECTED FROM SHIKOKU, JAPAN, AND SELECTION OF BREEDING MATERIALS BY THE APPLICATION OF THE PRINCIPAL COMPONENT ANALYSIS.

, 1967
Noboru Mochizuki, Tadakazu Okuno
openalex   +2 more sources

Comparing self‐reported race and genetic ancestry for identifying potential differentially methylated sites in endometrial cancer: insights from African ancestry proportions using machine learning models

Molecular Oncology, EarlyView.
Integrating ancestry, differential methylation analysis, and machine learning, we identified robust epigenetic signature genes (ESGs) and Core‐ESGs in Black and White women with endometrial cancer. Core‐ESGs (namely APOBEC1 and PLEKHG5) methylation levels were significantly associated with survival, with tumors from high African ancestry (THA) showing ...
Huma Asif, J. Julie Kim
wiley   +1 more source

A comparative study to examine principal component analysis and kernel principal component analysis-based weighting layer for convolutional neural networks

Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization
In the recent decay, the focus on processing signal data processing such as time series, images, and videos increased. The purpose of this processing is mainly forecasting, classification, and regression.
Amir Mehrabinezhad, Mohammad Teshnehlab, Arash Sharifi   +2 more
doaj   +1 more source

TEST OF RELIABILITY OF ARCH DAM BY PRINCIPAL COMPONENT ANALYSIS

, 1968
Ryoji Miike
openalex   +2 more sources