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Yves Moreau

Researcher at Katholieke Universiteit Leuven

Publications -  328
Citations -  25334

Yves Moreau is an academic researcher from Katholieke Universiteit Leuven. The author has contributed to research in topics: Gene & Cluster analysis. The author has an hindex of 63, co-authored 309 publications receiving 21467 citations. Previous affiliations of Yves Moreau include Karolinska Institutet & University of Liège.

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PlantCARE, a database of plant cis-acting regulatory elements and a portal to tools for in silico analysis of promoter sequences

TL;DR: New features have been implemented to search for plant cis-acting regulatory elements in a query sequence and links are now provided to a new clustering and motif search method to investigate clusters of co-expressed genes.
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BioMart and Bioconductor: a powerful link between biological databases and microarray data analysis

TL;DR: The biomaRt package provides a tight integration of large, public or locally installed BioMart databases with data analysis in Bioconductor creating a powerful environment for biological data mining.
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DECIPHER: Database of Chromosomal Imbalance and Phenotype in Humans Using Ensembl Resources

TL;DR: An interactive web-based database called DECIPHER (Database of Chromosomal Imbalance and Phenotype in Humans Using Ensembl Resources) which incorporates a suite of tools designed to aid the interpretation of submicroscopic chromosomal imbalance, inversions, and translocations.
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A human phenome-interactome network of protein complexes implicated in genetic disorders

TL;DR: A Bayesian predictor is developed that identifies novel candidates implicated in disorders such as retinitis pigmentosa, epithelial ovarian cancer, inflammatory bowel disease, amyotrophic lateral sclerosis, Alzheimer disease, type 2 diabetes and coronary heart disease.
Journal Article

Gene prioritization through genomic data fusion

TL;DR: In this article, a bioinformatics approach, together with a freely accessible, interactive and flexible software termed Endeavour, is presented to prioritize candidate genes underlying biological processes or diseases, based on their similarity to known genes involved in these phenomena.