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Pre-processing Agilent microarray data [PDF]
BMC Bioinformatics, 2007 Background Pre-processing methods for two-sample long oligonucleotide arrays, specifically the Agilent technology, have not been extensively studied. The goal of this study is to quantify some of the sources of error that affect measurement of expression
Schaeffer Edward +7 more
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Optimization of high molecular weight DNA extraction methods in shrimp for a long-read sequencing platform [PDF]
PeerJ, 2020 Marine organisms are important to global food security as they are the largest source of animal proteins feeding mankind. Genomics-assisted aquaculture can increase yield while preserving the environment to ensure sufficient and sustainable production ...
Pacharaporn Angthong +11 more
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Handling Big Microarray Data: A Novel Approach to Design Accurate Fuzzy-Based Medical Expert System
IEEE Access, 2023 The genes data produced by microarray experiments is complex in terms of dimensions and samples. It consumes a lot of computation power and time when it is processed for a disease analysis while working with an expert system.
Ganeshkumar Pugalendhi +3 more
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Therapeutic effects of Crataegus monogyna inhibitors against breast cancer
Frontiers in Pharmacology, 2023 Breast cancer is a silent killer disorder among women and a serious economic burden in healthcare management. Every 19 s, a woman is diagnosed with breast cancer, and every 74 s, a woman worldwide passes away from the disease.
Girish Meravanige Basavarajappa +6 more
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Normalizing DNA Microarray Data [PDF]
Current Issues in Molecular Biology, 2002 DNA microarrays are a powerful tool to investigate differential gene expression for thousands of genes simultaneously. Although DNA microarrays have been widely used to understand the critical events underlying growth, development, homeostasis, behavior and the onset of disease, the management of the resulting data has received little attention ...
Bilban, Martin +4 more
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Current Directions in Biomedical Engineering, 2023 Differentially Expressed Genes (DEGs) are treated as candidate biomarkers, and a small set of DEGs might be identified as biomarkers using either biological knowledge or data-driven approaches like machine learning and statistical analysis. In this study,
Sudharshan Ranga +4 more
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Cells, 2022 Atherosclerosis (AS) is a lipid-induced, chronic inflammatory, autoimmune disease affecting multiple arteries. Although much effort has been put into AS research in the past decades, it is still the leading cause of death worldwide.
Luling He +7 more
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Circulation Research, 2001 Over the last 10 to 20 years, the search for mechanisms responsible for cardiac remodeling during cardiac hypertrophy and failure has been hampered by the experimental tools available (primarily Western blot analysis and polymerase chain reaction). This is because these approaches only permit measurement of the expression levels of a few preselected ...
J S, Rao, M, Bond
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Identify the signature genes for diagnose of uveal melanoma by weight gene co-expression network analysis [PDF]
International Journal of Ophthalmology, 2015 AIM: To identify and understand the relationship between co-expression pattern and clinic traits in uveal melanoma, weighted gene co-expression network analysis (WGCNA) is applied to investigate the gene expression levels and patient clinic features ...
Kai Shi +6 more
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Transformations for cDNA Microarray Data [PDF]
Statistical Applications in Genetics and Molecular Biology, 2003 Two channel microarray data often contain systematic variations that can be minimized by data transformation prior to further analysis. The most commonly observed effects are revealed by viewing scatter plots of the logarithm of the ratio by the average logarithmic intensity of the two color channels (RI plots). In this paper we present a general model
Cui, Xiangqin +3 more
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