Showing 201 - 220 results of 702 for search '(((( selection microarray ) OR ( detection microarray ))) OR ( selective microarray ))', query time: 0.21s Refine Results
  1. 201

    Utilizing Machine Learning Techniques for Cancer Prediction and Classification based on Gene Expression Data by Mariwan Mahmood Hama Aziz, Sozan Abdullah Mahmood

    Published 2025-06-01
    “…Lately, several studies have delved into cancer classification by leveraging data mining techniques, machine learning algorithms, and statistical methods to thoroughly analyze high-dimensional datasets. Detecting cancer early by examining gene expression data is vital for providing effective patient care. …”
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    Article
  2. 202

    Advances in Research on Isothermal Signal Amplification Mediated MicroRNA Detection of Clinical Samples: Application to Disease Diagnosis by Yu Han, Xin Sun, Sheng Cai

    Published 2025-06-01
    “…However, the intrinsic characteristics of miRNAs, including their low abundance, short sequence lengths, and high family-specific sequence homology, render traditional detection methods such as Northern blot hybridization, microarray use, and reverse transcription quantitative PCR (RT-qPCR) inadequate for meeting the stringent requirements of clinical detection in biological samples, a task requiring accuracy, rapidity, high detection power, specificity, and cost-effectiveness. …”
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  3. 203

    Detection efficacy of non-invasive prenatal testing for copy number variations in the recurrent 17p12 region by ZHANG Lanlan, HAN Xu, LI Niu, WANG Jian, LI Shuyuan

    Published 2025-03-01
    “…Follow-up was conducted to assess the results of subsequent prenatal diagnosis and chromosomal microarray analysis (CMA) performed on peripheral blood from both the pregnant women and their husband. …”
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    Article
  4. 204

    SVseq discloses the genomic complexity of different prenatal, de novo, apparently balanced chromosome rearrangements detected by CMA and karyotype by Shengfang Qin, Xueyan Wang, Chun Chen, Jin Wang, Zhuo Zhang, Yan Yin, Xiangyou Leng

    Published 2025-05-01
    “…Methods Five children with BCRs detected through karyotyping and chromosome microarray analysis (CMA) during prenatal diagnoses were analyzed using SVseq technology. …”
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  5. 205

    Identification of Tumor‐Specific Surface Proteins Enables Quantification of Extracellular Vesicle Subtypes for Early Detection of Pancreatic Ductal Adenocarcinoma by Chen Zhao, Zhili Wang, Hyoyong Kim, Hui Kong, Junseok Lee, Jacqueline Ziqian Yang, Anmin Wang, Ryan Y. Zhang, Yong Ju, Jina Kim, Bing Feng, Dejun Liu, Yating Zhang, Zhenfang Wang, Yandong Zhang, Shujing Guo, Dekang Gao, James S. Tomlinson, Renjun Pei, Jipeng Wan, Stephen J. Pandol, Myung‐Shin Sim, Sungyong You, Ding Ma, Shaohua Lu, Na Sun, Hsian‐Rong Tseng, Yazhen Zhu

    Published 2025-06-01
    “…Abstract Pancreatic ductal adenocarcinoma (PDAC) is a leading cause of cancer‐related mortality, largely due to late‐stage diagnosis. Reliable early detection methods are critically needed. PDAC‐derived extracellular vesicles (EVs) carry molecules that reflect their parental tumor cells and are detectable in early disease stages, offering a promising noninvasive diagnostic approach. …”
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  6. 206
  7. 207

    Rapid Detection of Panton–Valentine Leukocidin Production in Clinical Isolates of <i>Staphylococcus aureus</i> from Saxony and Brandenburg and Their Molecular Characterisation by Elke Müller, Stefan Monecke, Marc Armengol Porta, Marco Vinicio Narvaez Encalada, Annett Reissig, Lukas Rüttiger, Percy Schröttner, Ilona Schwede, Hans-Herman Söffing, Alexander Thürmer, Ralf Ehricht

    Published 2025-03-01
    “…They were also characterized using DNA microarrays, facilitating the detection of virulence and resistance markers as well as the assignment to clonal complexes and epidemic/pandemic strains. …”
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  8. 208
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  11. 211

    Implementation of Valid HPV Diagnostics for the Early Detection of Cervical Cancer in Molecular Pathology: HPV 3.5 LCD-Array (Chipron GmbH) vs. PapilloCheck<sup>®</sup> (Greiner Bi... by Jan Jeroch, Melanie Winter, Anna Bieber, Agnes Boger, Christina Schmitt, Silvana Ebner, Morva Tahmasbi Rad, Henning Reis, Peter. J. Wild

    Published 2025-01-01
    “…This study compares the two hybridisation-based DNA-microarray systems “HPV 3.5 LCD-Array” (Chipron GmbH) and “PapilloCheck<sup>®</sup>” (Greiner Bio-One GmbH), based on their ability to detect and differentiate HPV infections in 42 different cervical smears. …”
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  12. 212

    The Features of a Humoral Immune Response Development during the Acute Phase of ixodes Tick-Borne Borreliosis (Based on Multiplex Analysis with the Immunochip) by V. G. Pomelova, E. I. Korenberg, T. I. Kuznetsova, N. S. Osin

    Published 2015-02-01
    “…Therefore, additional detection of IgM to recombinant proteins did not improve significantly the overall sensitivity of the latter PHOSPHAN variant. …”
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  13. 213

    Evaluating the potential of anti-dsRNA antibodies as an alternative viral sensing tool in encephalitides of different species by Madeleine de le Roi, Hannah Gerhards, Adnan Fayyad, Adnan Fayyad, Mathias Boelke, Stefanie Christine Becker, Asisa Volz, Ingo Gerhauser, Wolfgang Baumgärtner, Christina Puff

    Published 2025-03-01
    “…Molecular methods like multiplex PCR and microarrays are considered to be often less sensitive than Next Generation Sequencing, whereas the latter is time-consuming and costly. …”
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  14. 214

    A RNA-Seq Analysis of the Rat Supraoptic Nucleus Transcriptome: Effects of Salt Loading on Gene Expression. by Kory R Johnson, C C T Hindmarch, Yasmmyn D Salinas, YiJun Shi, Michael Greenwood, See Ziau Hoe, David Murphy, Harold Gainer

    Published 2015-01-01
    “…In addition, we compare the SON transcriptomes resolved by RNA-Seq methods with the SON transcriptomes determined by Affymetrix microarray methods in rats under the same osmotic conditions, and find that there are 6,466 genes present in the SON that are represented in both data sets, although 1,040 of the expressed genes were found only in the microarray data, and 2,762 of the expressed genes are selectively found in the RNA-Seq data and not the microarray data. …”
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  15. 215

    Genome-wide analysis of m6A-modified circRNAs in the mouse model of myocardial injury induced by obstructive sleep apnea by Jiuhuang Lan, Yuhui Wang, Chang Liu, Hongli Chen, Qingshi Chen

    Published 2025-04-01
    “…Methods Firstly, the expression profiles of m6A-modified circRNA in left ventricular tissue of the CIH mouse model were examined using circRNA microarray analysis. Then, the expression level of selected circrRNA was compared by folding change filtration, and the consistency between them and microarray results was verified by MeRIP-qPCR. …”
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  16. 216

    Using rule-based machine learning for candidate disease gene prioritization and sample classification of cancer gene expression data. by Enrico Glaab, Jaume Bacardit, Jonathan M Garibaldi, Natalio Krasnogor

    Published 2012-01-01
    “…A comparison with other benchmark microarray sample classifiers based on three diverse feature selection algorithms suggests that these evolutionary learning techniques can compete with state-of-the-art methods like support vector machines. …”
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  17. 217

    Mutation Spectrum of the ABCA4 Gene in a Greek Cohort with Stargardt Disease: Identification of Novel Mutations and Evidence of Three Prevalent Mutated Alleles by Kamakari Smaragda, Kokkinou Vassiliki, Koutsodontis George, Stamatiou Polixeni, Giatzakis Christoforos, Anastasakis Anastasios, Aslanides Ioannis Minas, Koukoula Stavrenia, Panagiotoglou Theoni, Datseris Ioannis, Tsilimbaris K. Miltiadis

    Published 2018-01-01
    “…MLPA analysis as well as sequencing of two regions in introns 30 and 36 reported earlier to harbor deep intronic disease-associated variants was used in 4 selected cases. Results. An overall detection rate of at least one mutant allele was achieved in 52 of the 59 patients (88.1%). …”
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  18. 218

    Evaluation of gene expression classification studies: factors associated with classification performance. by Putri W Novianti, Kit C B Roes, Marinus J C Eijkemans

    Published 2014-01-01
    “…The MAQC II study on cancer classification problems has found that performance was affected by factors such as the classification algorithm, cross validation method, number of genes, and gene selection method. In this paper, we study the hypothesis that the disease under study significantly determines which method is optimal, and that additionally sample size, class imbalance, type of medical question (diagnostic, prognostic or treatment response), and microarray platform are potentially influential. …”
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  19. 219

    Bioinformatics meets machine learning: identifying circulating biomarkers for vitiligo across blood and tissues by Qiyu Wang, Jingwei Yuan, Jingwei Yuan, Mengdi Zhang, Haiyan Jia, Hongjie Lu, Yan Wu

    Published 2025-05-01
    “…The exact aetiology and pathogenesis of vitiligo remain incompletely understood.MethodsFirst, a microarray dataset of blood samples from multiple patients with vitiligo was collected from GEO database.The limma package was used to analyze the microarray data and identify significant differentially expressed genes (DEGs). …”
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  20. 220

    Global gene expression profiling reveals SPINK1 as a potential hepatocellular carcinoma marker. by Aileen Marshall, Margus Lukk, Claudia Kutter, Susan Davies, Graeme Alexander, Duncan T Odom

    Published 2013-01-01
    “…Six genes identified by microarray as highly expressed in HH-HCC were confirmed by RT qPCR. …”
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