Results 11 to 20 of about 89,130 (269)

Navigating the microarray landscape: a comprehensive review of feature selection techniques and their applications [PDF]

Frontiers in Big Data
This 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, Azlan Mohd Zain, Yanjie Ren, Mahadi Bahari, Azurah A. Samah, Zuraini Binti Ali Shah, Norfadzlan Bin Yusup, Rozita Abdul Jalil, Azizah Mohamad, Nurulhuda Firdaus Mohd Azmi   +9 more
doaj   +2 more sources

Gene expression analysis of glucocorticoid-induced apoptosis by a gene microarray technique [PDF]

Nature Genetics, 2001
Gene expression analysis of glucocorticoid-induced apoptosis by a gene microarray ...
Huiling He, Michael H. Malone, Steven Ostrowski, Clark Distelhorst   +3 more
openalex   +2 more sources

Topographical Imaging Technique for Qualitative Analysis of Microarray Data [PDF]

BioTechniques, 2006
James Ch. Davis, Anna‐Lisa Paul, Robert J. Ferl, Mark W. Meisel   +3 more
openalex   +4 more sources

Using an attribute estimation technique for the analysis of microarray data

, 2003
We present an original method for the analysis of microarray data based on an attribute estimation technique. We show, in the context of radioactive environmental stress, that this method can be used to detect a small number of genes that, highly probably, are involved in the response to this stress in yeast.
Jérémie Mary, Guillaume Mercier, Jean‐Paul Comet, Antoine Cornuéjols, Christine Froidevaux, Marie Dutreix   +5 more
openalex   +3 more sources

Gene Ranking Techniques via Attribute Evaluation Algorithms for DNA Microarray Analysis [PDF]

International Conference on Aerospace Sciences and Aviation Technology, 2011
M. Al Senousy, H. El-Deeb, Kh. Badran, Ibrahim Ali Al-Khlil   +3 more
openalex   +2 more sources

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, Khamis A. Al-Karawi, Hatem E. Semary   +2 more
doaj   +1 more source

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 ...
BATTIATO, SEBASTIANO, G. DI BLASI, FARINELLA, GIOVANNI MARIA, GALLO, Giovanni, G. C. GUARNERA   +4 more
openaire   +2 more sources

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
doaj   +1 more source

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, Vallon-Christersson Johan, Svensson Martin, Häkkinen Jari   +3 more
doaj   +1 more source

Using rule-based machine learning for candidate disease gene prioritization and sample classification of cancer gene expression data.

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, Jaume Bacardit, Jonathan M Garibaldi, Natalio Krasnogor   +3 more
doaj   +1 more source