Search Results - "Pécot, Thierry"
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Deep learning tools and modeling to estimate the temporal expression of cell cycle proteins from 2D still images
Published in PLoS computational biology (01-03-2022)“…Automatic characterization of fluorescent labeling in intact mammalian tissues remains a challenge due to the lack of quantifying techniques capable of…”
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2
Testing independence between two random sets for the analysis of colocalization in bioimaging
Published in Biometrics (01-03-2020)“…Colocalization aims at characterizing spatial associations between two fluorescently tagged biomolecules by quantifying the co‐occurrence and correlation…”
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3
Two Distinct E2F Transcriptional Modules Drive Cell Cycles and Differentiation
Published in Cell reports (Cambridge) (18-06-2019)“…Orchestrating cell-cycle-dependent mRNA oscillations is critical to cell proliferation in multicellular organisms. Even though our understanding of…”
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4
Canonical and atypical E2Fs regulate the mammalian endocycle
Published in Nature cell biology (01-11-2012)“…The endocycle is a variant cell cycle consisting of successive DNA synthesis and gap phases that yield highly polyploid cells. Although essential for metazoan…”
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5
A quantitative approach for analyzing the spatio-temporal distribution of 3D intracellular events in fluorescence microscopy
Published in eLife (09-08-2018)“…Analysis of the spatial distribution of endomembrane trafficking is fundamental to understand the mechanisms controlling cellular dynamics, cell homeostasy,…”
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6
Deep learning provides high accuracy in automated chondrocyte viability assessment in articular cartilage using nonlinear optical microscopy
Published in Biomedical optics express (01-05-2021)“…Chondrocyte viability is a crucial factor in evaluating cartilage health. Most cell viability assays rely on dyes and are not applicable for or longitudinal…”
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7
Background Fluorescence Estimation and Vesicle Segmentation in Live Cell Imaging With Conditional Random Fields
Published in IEEE transactions on image processing (01-02-2015)“…Image analysis applied to fluorescence live cell microscopy has become a key tool in molecular biology since it enables to characterize biological processes in…”
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8
A deep learning segmentation strategy that minimizes the amount of manually annotated images [version 1; peer review: 2 approved with reservations]
Published in F1000 research (2021)“…Deep learning has revolutionized the automatic processing of images. While deep convolutional neural networks have demonstrated astonishing segmentation…”
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9
Artificial Intelligence in Predicting Microsatellite Instability and KRAS, BRAF Mutations from Whole-Slide Images in Colorectal Cancer: A Systematic Review
Published in Diagnostics (Basel) (31-12-2023)“…Mismatch repair deficiency (d-MMR)/microsatellite instability (MSI), , and mutational status are crucial for treating advanced colorectal cancer patients…”
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10
Identifying survival associated morphological features of triple negative breast cancer using multiple datasets
Published in Journal of the American Medical Informatics Association : JAMIA (01-07-2013)“…Biomarkers for subtyping triple negative breast cancer (TNBC) are needed given the absence of responsive therapy and relatively poor prediction of survival…”
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11
Counting-Based Particle Flux Estimation for Traffic Analysis in Live Cell Imaging
Published in IEEE journal of selected topics in signal processing (01-02-2016)“…A quantitative analysis of the dynamic contents in fluorescence time-lapse microscopy is crucial to decipher the molecular mechanisms involved in cell…”
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12
Capturing variations in nuclear phenotypes
Published in Journal of computational science (01-09-2019)“…•We propose a way for 3D quantification of nuclear phenotypes in a tissue microenvironment using shape, texture and contextual features.•We implement on a…”
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13
A signal processing approach for enriched region detection in RNA polymerase II ChIP-seq data
Published in BMC bioinformatics (13-03-2012)“…RNA polymerase II (PolII) is essential in gene transcription and ChIP-seq experiments have been used to study PolII binding patterns over the entire genome…”
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14
Non-parametric population analysis of cellular phenotypes
Published in Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention (2011)“…Methods to quantify cellular-level phenotypic differences between genetic groups are a key tool in genomics research. In disease processes such as cancer,…”
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15
Transcriptome regulation and chromatin occupancy by E2F3 and MYC in mice
Published in Scientific data (16-02-2016)“…E2F3 and MYC are transcription factors that control cellular proliferation. To study their mechanism of action in the context of a regenerating tissue, we…”
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16
Identifying nuclear phenotypes using semi-supervised metric learning
Published in Information processing in medical imaging : proceedings of the ... conference (2011)“…In systems-based approaches for studying processes such as cancer and development, identifying and characterizing individual cells within a tissue is the first…”
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17
Estimation of the flow of particles within a partition of the image domain in fluorescence video-microscopy
Published in 2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI) (01-04-2014)“…Automatic analysis of the dynamic content in fluorescence video-microscopy is crucial for understanding molecular mechanisms involved in cell functions. In…”
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Conference Proceeding -
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An end-to-end pipeline based on open source deep learning tools for reliable analysis of complex 3D images of ovaries
Published in Development (Cambridge) (01-04-2023)“…Computational analysis of bio-images by deep learning (DL) algorithms has made exceptional progress in recent years and has become much more accessible to…”
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19
The coordination of spindle-positioning forces during the asymmetric division of the Caenorhabditis elegans zygote
Published in EMBO reports (05-05-2021)“…In Caenorhabditis elegans zygote, astral microtubules generate forces essential to position the mitotic spindle, by pushing against and pulling from the…”
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20
Deep Learning for Detecting BRCA Mutations in High-Grade Ovarian Cancer Based on an Innovative Tumor Segmentation Method From Whole Slide Images
Published in Modern pathology (01-11-2023)“…BRCA1 and BRCA2 genes play a crucial role in repairing DNA double-strand breaks through homologous recombination. Their mutations represent a significant…”
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