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Eric Biot

dblp:86/479 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2010
0000-0003-3864-0655ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 2

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
gene expression analysis
0.112010
ANAIS: Analysis of NimbleGen Arrays Interface · Bioinform. 2010
Bioinformatics and computational biology › gene expression analysis › microarray data preprocessing
microarray data processing
0.112010
ANAIS: Analysis of NimbleGen Arrays Interface · Bioinform. 2010

Methods — techniques the papers use, named apart from their topics

normalization · 0.1differential expression analysis · 0.1clustering · 0.1
YearPublicationVenuePosition
2010 ANAIS: Analysis of NimbleGen Arrays Interface
abstract
UNLABELLED: ANAIS is a user-friendly web-based tool for the processing of NimbleGen expression data. The interface reads single-channel microarray files generated by NimbleGen platforms and produces easily interpretable graphical and numerical results. It provides biologists six turnkey analysis modules-normalization, probe to gene, quality controls, differential expression, detection, queries and clustering-to explore quickly, freely and without the need for computer programming, NimbleGen transcriptome data. AVAILABILITY: http://anais.versailles.inra.fr.
Adeline Simon, Eric Biot
Bioinform.2
2010 Statistical Analysis of 3D Images Detects Regular Spatial Distributions of Centromeres and Chromocenters in Animal and Plant Nuclei
abstract
In eukaryotes, the interphase nucleus is organized in morphologically and/or functionally distinct nuclear "compartments". Numerous studies highlight functional relationships between the spatial organization of the nucleus and gene regulation. This raises the question of whether nuclear organization principles exist and, if so, whether they are identical in the animal and plant kingdoms. We addressed this issue through the investigation of the three-dimensional distribution of the centromeres and chromocenters. We investigated five very diverse populations of interphase nuclei at different differentiation stages in their physiological environment, belonging to rabbit embryos at the 8-cell and blastocyst stages, differentiated rabbit mammary epithelial cells during lactation, and differentiated cells of Arabidopsis thaliana plantlets. We developed new tools based on the processing of confocal images and a new statistical approach based on G- and F- distance functions used in spatial statistics. Our original computational scheme takes into account both size and shape variability by comparing, for each nucleus, the observed distribution against a reference distribution estimated by Monte-Carlo sampling over the same nucleus. This implicit normalization allowed similar data processing and extraction of rules in the five differentiated nuclei populations of the three studied biological systems, despite differences in chromosome number, genome organization and heterochromatin content. We showed that centromeres/chromocenters form significantly more regularly spaced patterns than expected under a completely random situation, suggesting that repulsive constraints or spatial inhomogeneities underlay the spatial organization of heterochromatic compartments. The proposed technique should be useful for identifying further spatial features in a wide range of cell types.
Philippe Andrey, Kiên Kiêu, Clémence Kress, Gaëtan Lehmann, Leïla Tirichine, Zichuan Liu, Eric Biot, Pierre-Gaël Adenot, Cathy Hue-Beauvais, Nicole Houba-Hérin, Véronique Duranthon, Eve Devinoy, Nathalie Beaujean, Valérie Gaudin, Yves Maurin, Pascale Debey
PLoS Comput. Biol.7