References of "Jeanray, Nathalie"
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See detailPhenotype Classification of Zebrafish Embryos by Supervised Learning
Jeanray, Nathalie ULg; Marée, Raphaël ULg; Pruvot, Benoist et al

in PLoS ONE (2014), soumis

Zebrafish is increasingly used to assess biological properties of chemical substances and thus is becoming a specific tool for toxicological and pharmacological studies. The effects of chemical substances ... [more ▼]

Zebrafish is increasingly used to assess biological properties of chemical substances and thus is becoming a specific tool for toxicological and pharmacological studies. The effects of chemical substances on embryo survival and development are generally evaluated manually through microscopic observation by an expert and documented by several typical photographs. Here, we present a methodology to automatically classify brightfield images of wildtype zebrafish embryos according to their defects by using an image analysis approach based on supervised machine learning. We show that, compared to manual classification, automatic classification results in 90 to 100 % agreement with consensus voting of biological experts in nine out of eleven considered defects in 3 days old zebrafish larvae. Automation of the analysis and classification of zebrafish embryo pictures reduces the workload and time required for the biological expert and increases the reproducibility and objectivity of this classification. [less ▲]

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See detailA panel of biological tests reveals developmental effects of pharmaceutical pollutants on late stage zebrafish embryos.
Pruvot, Benoist ULg; Quiroz O' Donova, Yobhana ULg; Voncken, Audrey ULg et al

in Reproductive Toxicology (2012)

Standard toxicological assays using the zebrafish model system evaluate lethality and teratogenicity upon exposure during the first two days after fertilization. We tested the biological effects of ... [more ▼]

Standard toxicological assays using the zebrafish model system evaluate lethality and teratogenicity upon exposure during the first two days after fertilization. We tested the biological effects of several widely used drugs on zebrafish by acute treatment for 24hours starting at late embryonic stages, between 48 and 72hours post-fertilization. For 4 out of 6 compounds, we observed a higher sensitivity of late stage zebrafish embryos for general toxicity (lethality) compared to younger embryos. Morphological defects such as edema, body curvature, delayed growth, decreased heart rate and locomotion were observed for each of the compounds tested, often at sublethal concentrations. Gene expression studies on a set of four selected genes revealed a specific regulatory pattern for the different compounds tested. Our results allow us to compare various toxicological endpoints and may contribute to the design of a rational high throughput approach using the zebrafish model. [less ▲]

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See detailPhenotype Classification of Zebrafish Embryos by Supervised Learning
Jeanray, Nathalie ULg; Marée, Raphaël ULg; Pruvot, Benoist ULg et al

Conference (2011, September 02)

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See detailZebrafish Skeleton Measurements using Image Analysis and Machine Learning Methods
Stern, Olivier ULg; Marée, Raphaël ULg; Aceto, Jessica ULg et al

Poster (2011, May 20)

The zebrafish is a model organism for biological studies on development and gene function. Our work aims at automating the detection of the cartilage skeleton and measuring several distances and angles to ... [more ▼]

The zebrafish is a model organism for biological studies on development and gene function. Our work aims at automating the detection of the cartilage skeleton and measuring several distances and angles to quantify its development following different experimental conditions. [less ▲]

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See detailAutomatic localization of interest points in zebrafish images with tree-based methods
Stern, Olivier ULg; Marée, Raphaël ULg; Aceto, Jessica ULg et al

in Proceedings of the 6th IAPR International Conference on Pattern Recognition in Bioinformatics (2011)

In many biological studies, scientists assess effects of experimental conditions by visual inspection of microscopy images. They are able to observe whether a protein is expressed or not, if cells are ... [more ▼]

In many biological studies, scientists assess effects of experimental conditions by visual inspection of microscopy images. They are able to observe whether a protein is expressed or not, if cells are going through normal cell cycles, how organisms evolve in different experimental conditions, etc. But, with the large number of images acquired in high-throughput experiments, this manual inspection becomes lengthy, tedious and error-prone. In this paper, we propose to automatically detect specific interest points in microscopy images using machine learning methods with the aim of performing automatic morphometric measurements in the context of Zebrafish studies. We systematically evaluate variants of ensembles of classification and regression trees on four datasets corresponding to different imaging modalities and experimental conditions. Our results show that all variants are effective, with a slight advantage for multiple output methods, which are more robust to parameter choices. [less ▲]

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