Association Analysis Techniques for Discovering Functional Modules from Microarray Data [PDF]
Nature Precedings, 2008 An application of great interest in microarray data analysis is the identification of a group of genes that show very similar patterns of expression in a data set, and are expected to represent groups of genes that perform common/similar functions, also ...
Gaurav Pandey +3 more
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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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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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Microarray Technique, Analysis, and Applications in Dermatology [PDF]
Journal of Investigative Dermatology, 2013 The Human Genome Project, completed in 2003, identified the sequence of the approximately 25,000 genes that comprise the human genome. Knowledge of the structure of the human genome opened the doors to studying the actual function of specific genes, which is necessary to understanding health and disease.
Villaseñor-Park, Jennifer +1 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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Adaptive techniques for microarray image analysis with related quality assessment [PDF]
Journal of Electronic Imaging, 2007 We propose novel techniques for microarray image analysis. In particular, we describe an overall pipeline able to solve the most common problems of microarray image analysis. We pro- pose the microarray image rotation algorithm (MIRA) and the statis- tical gridding pipeline (SGRIP) as two advanced modules devoted to restoring the original microarray ...
Sebastiano Battiato +4 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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