Integrating image processing with deep convolutional neural networks for gene selection and cancer classification using microarray data [PDF]
Scientific ReportsMicroarray technology has revolutionized cancer genomics by enabling the simultaneous analysis of thousands of gene expressions, providing critical insights into gene regulation and disease mechanisms.
Yuanyuan Zhang, Jing Chen, Chong Zhang
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Application of chromosome microarray analysis and karyotyping in fetal cardiac abnormalities [PDF]
Frontiers in GeneticsObjectiveChromosome microarray analysis (CMA) and karyotyping are two important genetic testing techniques used in prenatal diagnosis. This study aims to evaluate the value of chromosome microarray analysis and karyotyping in the diagnosis of fetal ...
Yun Guo +3 more
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Navigating the microarray landscape: a comprehensive review of feature selection techniques and their applications [PDF]
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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Deep Learning-Based Prediction of Alzheimer’s Disease Using Microarray Gene Expression Data
Biomedicines, 2023 Alzheimer’s disease is a genetically complex disorder, and microarray technology provides valuable insights into it. However, the high dimensionality of microarray datasets and small sample sizes pose challenges. Gene selection techniques have emerged as
Mahmoud M. Abdelwahab +2 more
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Geometric interpretation of gene coexpression network analysis.
PLoS Computational Biology, 2008 THE MERGING OF NETWORK THEORY AND MICROARRAY DATA ANALYSIS TECHNIQUES HAS SPAWNED A NEW FIELD: gene coexpression network analysis. While network methods are increasingly used in biology, the network vocabulary of computational biologists tends to be far ...
Steve Horvath, Jun Dong
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MAPPI-DAT : data management and analysis for protein-protein interaction data from the high-throughput MAPPIT cell microarray platform [PDF]
, 2017 Protein-protein interaction (PPI) studies have dramatically expanded our knowledge about cellular behaviour and development in different conditions. A multitude of high-throughput PPI techniques have been developed to achieve proteome-scale coverage for ...
De Puysseleyr, Veronic +8 more
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Copasetic analysis: a framework for the blind analysis of microarray imagery [PDF]
, 2004 The official published version can be found at the link below.From its conception, bioinformatics has been a multidisciplinary field which blends domain expert knowledge with new and existing processing techniques, all of which are focused on a common ...
Berkhin +13 more
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BASE - 2nd generation software for microarray data management and analysis
BMC Bioinformatics, 2009 Background Microarray experiments are increasing in size and samples are collected asynchronously over long time. Available data are re-analysed as more samples are hybridized.
Nordborg Nicklas +3 more
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Information visualization for DNA microarray data analysis: A critical review [PDF]
, 2008 Graphical representation may provide effective means of making sense of the complexity and sheer volume of data produced by DNA microarray experiments that monitor the expression patterns of thousands of genes simultaneously.
Kuljis, J, Liu, X, Zhang, L
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Paradigm of tunable clustering using binarization of consensus partition matrices (Bi-CoPaM) for gene discovery [PDF]
, 2013 Copyright @ 2013 Abu-Jamous et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and ...
A Strehl +39 more
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