Výsledky vyhledávání - "Argiris Sakellariou"

mAPKL: R/ Bioconductor package for detecting gene exemplars and revealing their characteristics

Autor: Argiris Sakellariou, George M. Spyrou

Publikováno v: BMC Bioinformatics

Background So far many algorithms have been proposed towards the detection of significant genes in microarray analysis problems. Several of those approaches are freely available as R-packages though their engagement in gene expression analysis by non

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::18e79a2b6a8a4eecaa6f701d296066ca
https://doi.org/10.1186/s12859-015-0719-5

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A Web-based database of genetic association studies in cutaneous melanoma enhanced with network-driven data exploration tools

Autor: Alexander J. Stratigos, Lars Bertram, Marilena M. Bourdakou, Foteini Chatzinasiou, I. Stefanaki, John P. A. Ioannidis, Emmanouil Athanasiadis, Christina M. Lill, Evangelos Evangelou, Katerina P. Kypreou, Argiris Sakellariou, Kyriaki Antonopoulou, George M. Spyrou

Publikováno v: Database : The Journal of Biological Databases and Curation
Database: The Journal of Biological Databases and Curation

The publicly available online database MelGene provides a comprehensive, regularly updated, collection of data from genetic association studies in cutaneous melanoma (CM), including random-effects meta-analysis results of all eligible polymorphisms.

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::904ef3d90e35aeb69c3e287f87363d63
https://hdl.handle.net/11858/00-001M-0000-0026-AFF2-511858/00-001M-0000-0026-AFF4-1

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Combining multiple hypothesis testing and affinity propagation clustering leads to accurate, robust and sample size independent classification on gene expression data

Autor: Argiris Sakellariou, George M. Spyrou, Despina Sanoudou

Publikováno v: BMC Bioinformatics, Vol 13, Iss 1, p 270 (2012)
BMC Bioinformatics; Vol 13
BMC Bioinformatics

Background A feature selection method in microarray gene expression data should be independent of platform, disease and dataset size. Our hypothesis is that among the statistically significant ranked genes in a gene list, there should be clusters of

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dccc32cfb5347812e3bb3abfb520e54c
https://doi.org/10.1186/1471-2105-13-270

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Investigating the minimum required number of genes for optimum classification of myopathy microarray data

Autor: Argiris Sakellariou, Despina Sanoudou, George M. Spyrou

Publikováno v: 2009 9th International Conference on Information Technology and Applications in Biomedicine.

The investigation of potential microarray markers, which in turn will speed up the molecular analysis and provide reliable results on the benefit of patient care is of significant importance. Feature selection techniques, which aim at minimizing the

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::294cf8575a51bd0ccc95cc6794edbdd5
https://doi.org/10.1109/itab.2009.5394402

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