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Alain Coletta

Researcher at Université libre de Bruxelles

Publications -  13
Citations -  1389

Alain Coletta is an academic researcher from Université libre de Bruxelles. The author has contributed to research in topics: Bioconductor & Feature selection. The author has an hindex of 9, co-authored 13 publications receiving 1147 citations. Previous affiliations of Alain Coletta include University of Manchester & Vrije Universiteit Brussel.

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A Survey on Filter Techniques for Feature Selection in Gene Expression Microarray Analysis

TL;DR: This survey focuses on filter feature selection methods for informative feature discovery in gene expression microarray (GEM) analysis, which is also known as differentially expressed genes (DEGs) discovery, gene prioritization, or biomarker discovery, and presents them in a unified framework.
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Batch effect removal methods for microarray gene expression data integration: a survey

TL;DR: Methods designed to combine genomic data recorded from microarray gene expression (MAGE) experiments are reviewed in a unified framework together with a wide range of evaluation tools, which are mandatory in assessing the efficiency and the quality of the data integration process.
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Low-complexity regions within protein sequences have position-dependent roles.

TL;DR: The results suggest not only that LCRs may be involved in flexible binding associated with specific functions, but also that their positions within a sequence may be important in determining both their binding properties and their biological roles.
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The PRINTS database: a fine-grained protein sequence annotation and analysis resource--its status in 2012.

TL;DR: The PRINTS database, now in its 21st year, houses a collection of diagnostic protein family ‘fingerprints’, whose unique inter-relationships provide distinctive signatures for particular protein families and structural/functional domains, and a number of recent developments are introduced.
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Unlocking the potential of publicly available microarray data using inSilicoDb and inSilicoMerging R/Bioconductor packages

TL;DR: The newly released inSilicoMerging R/Bioconductor package allows consistent retrieval, integration and analysis of publicly available microarray gene expression data sets and enables researchers to fully explore the potential of combining gene expressionData for downstream analysis.