Results 61 to 70 of about 568,857 (297)
Simple empirical models of classifying patients from microarray data
Kuwait Journal of Science, 2019 There have been tremendous advances in bioinformatics in recent years. One of these is the use of microarrays for collecting Big Data. This paper reports on the work carried out by the author in devising models to classify patients by conducting ...
Alan Oxley
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EURASIP Journal on Advances in Signal Processing, 2004 This paper focuses on the stability-based approach for estimating the number of clusters in microarray data. The cluster stability approach amounts to performing clustering successively over random subsets of the available data and evaluating an index ...
Giurcăneanu Ciprian Doru +1 more
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Peroxidasin enables melanoma immune escape by inhibiting natural killer cell cytotoxicity
Molecular Oncology, EarlyView.Peroxidasin (PXDN) is secreted by melanoma cells and binds the NK cell receptor NKG2D, thereby suppressing NK cell activation and cytotoxicity. PXDN depletion restores NKG2D signaling and enables effective NK cell–mediated melanoma killing. These findings identify PXDN as a previously unrecognized immune evasion factor and a potential target to improve
Hsu‐Min Sung +17 more
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BarekengOvarian cancer can be identified from microarray data using machine learning. Many studies only focus on improving the machine learning classification algorithms to achieve higher performance.
Ni Kadek Emik Sapitri +2 more
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Molecular Oncology, EarlyView.To integrate multiple transcriptomics data with severe batch effects for identifying MB subtypes, we developed a novel and accurate computational method named RaMBat, which leveraged subtype‐specific gene expression ranking information instead of absolute gene expression levels to address batch effects of diverse data sources.
Mengtao Sun, Jieqiong Wang, Shibiao Wan
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DiagnosticsBackground/Objectives: Cancer classification using microarray datasets presents a significant challenge due to their extremely high dimensionality. This complexity necessitates advanced optimization methods for effective gene selection.
Shahad Alkamli, Hala Alshamlan
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Reproducibility of microarray data: a further analysis of microarray quality control (MAQC) data
BMC Bioinformatics, 2007 Background Many researchers are concerned with the comparability and reliability of microarray gene expression data. Recent completion of the MicroArray Quality Control (MAQC) project provides a unique opportunity to assess reproducibility across ...
Lin Chien-Ju +4 more
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Molecular Oncology, EarlyView.Meta‐transcriptome analysis identified FGF19 as a peptide enteroendocrine hormone associated with colorectal cancer prognosis. In vivo xenograft models showed release of FGF19 into the blood at levels that correlated with tumor volumes. Tumoral‐FGF19 altered murine liver metabolism through FGFR4, thereby reducing bile acid synthesis and increasing ...
Jordan M. Beardsley +5 more
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Frontiers in Big DataThis review systematically summarizes recent advances in microarray feature selection techniques and their applications in biomedical research. It addresses the challenges posed by the high dimensionality and noise of microarray data, aiming to integrate
Fangling Wang +9 more
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Classification and prediction of dengue fever from microarray samples by LDA based on PPI network [PDF]
Network Biology, 2018 Modern Bioinformatics tools have a tremendous contribution in gene analysis, Protein-Protein Interaction (PPI) Network creation and Drug design. It's been a big challenge to pick out a small subset of informative data from a large microarray dataset and ...
Nahida Habib +2 more
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