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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PLoS ONE, 2012 Microarray data analysis has been shown to provide an effective tool for studying cancer and genetic diseases. Although classical machine learning techniques have successfully been applied to find informative genes and to predict class labels for new ...
Enrico Glaab +3 more
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Computational Intelligence Techniques for Classification in Microarray Analysis [PDF]
, 2010 During the last few years there has been a growing need for using computational intelligence techniques to analyze microarray data. The aim of the system presented in this study is to provide innovative decision support techniques for classifying data from microarrays and for extracting knowledge about the classification process.
Juan F. De Paz +3 more
openaire +3 more sources
A Fully Automated Gridding Technique for Real Composite cDNA Microarray Images
IEEE Access, 2020 Genome-wide screening using microarrays of DNA will be of great use in the early diagnosis of diseases such as cancer and HIV. It also makes use of gene discovery, pharmacogenomics, toxicogenomics, and nutrigenomics for other applications.
Steffy Maria Joseph, P. S. Sathidevi
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High throughput genetic analysis of congenital myasthenic syndromes using resequencing microarrays. [PDF]
PLoS ONE, 2007 The use of resequencing microarrays for screening multiple, candidate disease loci is a promising alternative to conventional capillary sequencing. We describe the performance of a custom resequencing microarray for mutational analysis of Congenital ...
Lisa Denning +5 more
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