Publications by authors named "Thierry Pecót"

16 Publications

  • Page 1 of 1

Testing independence between two random sets for the analysis of colocalization in bioimaging.

Biometrics 2020 03 11;76(1):36-46. Epub 2019 Aug 11.

Centre Rennes-Bretagne Atlantique, SERPICO Project Team, Inria, Rennes, France.

Colocalization aims at characterizing spatial associations between two fluorescently tagged biomolecules by quantifying the co-occurrence and correlation between the two channels acquired in fluorescence microscopy. Colocalization is presented either as the degree of overlap between the two channels or the overlays of the red and green images, with areas of yellow indicating colocalization of the molecules. This problem remains an open issue in diffraction-limited microscopy and raises new challenges with the emergence of superresolution imaging, a microscopic technique awarded by the 2014 Nobel prize in chemistry. We propose GcoPS, for Geo-coPositioning System, an original method that exploits the random sets structure of the tagged molecules to provide an explicit testing procedure. Our simulation study shows that GcoPS unequivocally outperforms the best competitive methods in adverse situations (noise, irregularly shaped fluorescent patterns, and different optical resolutions). GcoPS is also much faster, a decisive advantage to face the huge amount of data in superresolution imaging. We demonstrate the performances of GcoPS on two biological real data sets, obtained by conventional diffraction-limited microscopy technique and by superresolution technique, respectively.
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http://dx.doi.org/10.1111/biom.13115DOI Listing
March 2020

Two Distinct E2F Transcriptional Modules Drive Cell Cycles and Differentiation.

Cell Rep 2019 06 23;27(12):3547-3560.e5. Epub 2019 May 23.

Department of Biochemistry and Molecular Biology, Hollings Cancer Center, Medical University of South Carolina, Charleston, SC 29425, USA. Electronic address:

Orchestrating cell-cycle-dependent mRNA oscillations is critical to cell proliferation in multicellular organisms. Even though our understanding of cell-cycle-regulated transcription has improved significantly over the last three decades, the mechanisms remain untested in vivo. Unbiased transcriptomic profiling of G, G-S, and S-G-M sorted cells from FUCCI mouse embryos suggested a central role for E2Fs in the control of cell-cycle-dependent gene expression. The analysis of gene expression and E2F-tagged knockin mice with tissue imaging and deep-learning tools suggested that post-transcriptional mechanisms universally coordinate the nuclear accumulation of E2F activators (E2F3A) and canonical (E2F4) and atypical (E2F8) repressors during the cell cycle in vivo. In summary, we mapped the spatiotemporal expression of sentinel E2F activators and canonical and atypical repressors at the single-cell level in vivo and propose that two distinct E2F modules relay the control of gene expression in cells actively cycling (E2F3A-8-4) and exiting the cycle (E2F3A-4) during mammalian development.
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http://dx.doi.org/10.1016/j.celrep.2019.05.004DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6673649PMC
June 2019

A quantitative approach for analyzing the spatio-temporal distribution of 3D intracellular events in fluorescence microscopy.

Elife 2018 08 9;7. Epub 2018 Aug 9.

Serpico Team-Project, Inria, Centre Rennes-Bretagne Atlantique, Rennes, France.

Analysis of the spatial distribution of endomembrane trafficking is fundamental to understand the mechanisms controlling cellular dynamics, cell homeostasy, and cell interaction with its external environment in normal and pathological situations. We present a semi-parametric framework to quantitatively analyze and visualize the spatio-temporal distribution of intracellular events from different conditions. From the spatial coordinates of intracellular features such as segmented subcellular structures or vesicle trajectories, QuantEv automatically estimates weighted densities that are easy to interpret and performs a comprehensive statistical analysis from distribution distances. We apply this approach to study the spatio-temporal distribution of moving Rab6 fluorescently labeled membranes with respect to their direction of movement in crossbow- and disk-shaped cells. We also investigate the position of the generating hub of Rab11-positive membranes and the effect of actin disruption on Rab11 trafficking in coordination with cell shape.
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http://dx.doi.org/10.7554/eLife.32311DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6085121PMC
August 2018

Transcriptome regulation and chromatin occupancy by E2F3 and MYC in mice.

Sci Data 2016 Feb 16;3:160008. Epub 2016 Feb 16.

Department of Molecular Virology, Immunology and Medical Genetics, College of Medicine, Columbus, Ohio 43210, USA.

E2F3 and MYC are transcription factors that control cellular proliferation. To study their mechanism of action in the context of a regenerating tissue, we isolated both proliferating (crypts) and non-dividing (villi) cells from wild-type and Rb depleted small intestines of mice and performed ChIP-exo-seq (chromatin immunoprecipitation combined with lambda exonuclease digestion followed by high-throughput sequencing). The genome-wide chromatin occupancy of E2F3 and MYC was determined by mapping sequence reads to the genome and predicting preferred binding sites (peaks). Binding sites could be accurately identified within small regions of only 24 bp-28 bp long, highlighting the precision to which binding peaks can be identified by ChIP-exo-seq. Forty randomly selected E2F3- and MYC-specific binding sites were validated by ChIP-PCR. In addition, we also presented gene expression data sets from wild type, Rb-, E2f3- and Myc-depleted crypts and villi within this manuscript. These represent comprehensive and validated datasets that can be integrated to identify putative direct targets of E2F3 and MYC involved in the control of cellular proliferation in normal and Rb-deficient small intestines.
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http://dx.doi.org/10.1038/sdata.2016.8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4755127PMC
February 2016

Noncatalytic PTEN missense mutation predisposes to organ-selective cancer development in vivo.

Genes Dev 2015 Aug;29(16):1707-20

Solid Tumor Biology Program, James Comprehensive Cancer Center, The Ohio State University, Columbus, Ohio 43210, USA; Department of Molecular Genetics, College of Arts and Sciences, The Ohio State University, Columbus, Ohio 43210, USA; Department of Molecular Virology, Immunology, and Medical Genetics, College of Medicine, The Ohio State University, Columbus, Ohio 43210, USA;

Inactivation of phosphatase and tensin homology deleted on chromosome 10 (PTEN) is linked to increased PI3K-AKT signaling, enhanced organismal growth, and cancer development. Here we generated and analyzed Pten knock-in mice harboring a C2 domain missense mutation at phenylalanine 341 (Pten(FV)), found in human cancer. Despite having reduced levels of PTEN protein, homozygous Pten(FV/FV) embryos have intact AKT signaling, develop normally, and are carried to term. Heterozygous Pten(FV/+) mice develop carcinoma in the thymus, stomach, adrenal medulla, and mammary gland but not in other organs typically sensitive to Pten deficiency, including the thyroid, prostate, and uterus. Progression to carcinoma in sensitive organs ensues in the absence of overt AKT activation. Carcinoma in the uterus, a cancer-resistant organ, requires a second clonal event associated with the spontaneous activation of AKT and downstream signaling. In summary, this PTEN noncatalytic missense mutation exposes a core tumor suppressor function distinct from inhibition of canonical AKT signaling that predisposes to organ-selective cancer development in vivo.
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http://dx.doi.org/10.1101/gad.262568.115DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4561480PMC
August 2015

Redeployment of Myc and E2f1-3 drives Rb-deficient cell cycles.

Nat Cell Biol 2015 Aug 20;17(8):1036-48. Epub 2015 Jul 20.

1] Department of Molecular Virology, Immunology and Medical Genetics, College of Medicine, The Ohio State University, Columbus, Ohio 43210, USA [2] Department of Molecular Genetics, College of Biological Sciences, The Ohio State University, Columbus, Ohio 43210, USA [3] Comprehensive Cancer Center, The Ohio State University, Columbus, Ohio 43210, USA.

Robust mechanisms to control cell proliferation have evolved to maintain the integrity of organ architecture. Here, we investigated how two critical proliferative pathways, Myc and E2f, are integrated to control cell cycles in normal and Rb-deficient cells using a murine intestinal model. We show that Myc and E2f1-3 have little impact on normal G1-S transitions. Instead, they synergistically control an S-G2 transcriptional program required for normal cell divisions and maintaining crypt-villus integrity. Surprisingly, Rb deficiency results in the Myc-dependent accumulation of E2f3 protein and chromatin repositioning of both Myc and E2f3, leading to the 'super activation' of a G1-S transcriptional program, ectopic S phase entry and rampant cell proliferation. These findings reveal that Rb-deficient cells hijack and redeploy Myc and E2f3 from an S-G2 program essential for normal cell cycles to a G1-S program that re-engages ectopic cell cycles, exposing an unanticipated addiction of Rb-null cells on Myc.
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http://dx.doi.org/10.1038/ncb3210DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4526313PMC
August 2015

Actin grips: circular actin-rich cytoskeletal structures that mediate the wrapping of polymeric microfibers by endothelial cells.

Biomaterials 2015 Jun 18;52:395-406. Epub 2015 Mar 18.

Department of Internal Medicine, The Ohio State University, Columbus, OH, 43210, USA. Electronic address:

Interaction of endothelial-lineage cells with three-dimensional substrates was much less studied than that with flat culture surfaces. We investigated the in vitro attachment of both mature endothelial cells (ECs) and of less differentiated EC colony-forming cells to poly-ε-capro-lactone (PCL) fibers with diameters in 5-20 μm range ('scaffold microfibers', SMFs). We found that notwithstanding the poor intrinsic adhesiveness to PCL, both cell types completely wrapped the SMFs after long-term cultivation, thus attaining a cylindrical morphology. In this system, both EC types grew vigorously for more than a week and became increasingly more differentiated, as shown by multiplexed gene expression. Three-dimensional reconstructions from multiphoton confocal microscopy images using custom software showed that the filamentous (F) actin bundles took a conspicuous ring-like organization around the SMFs. Unlike the classical F-actin-containing stress fibers, these rings were not associated with either focal adhesions or intermediate filaments. We also demonstrated that plasma membrane boundaries adjacent to these circular cytoskeletal structures were tightly yet dynamically apposed to the SMFs, for which reason we suggest to call them 'actin grips'. In conclusion, we describe a particular form of F-actin assembly with relevance for cytoskeletal organization in response to biomaterials, for endothelial-specific cell behavior in vitro and in vivo, and for tissue engineering.
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http://dx.doi.org/10.1016/j.biomaterials.2015.02.034DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4418805PMC
June 2015

Background fluorescence estimation and vesicle segmentation in live cell imaging with conditional random fields.

IEEE Trans Image Process 2015 Feb 12;24(2):667-80. Epub 2014 Dec 12.

Image analysis applied to fluorescence live cell microscopy has become a key tool in molecular biology since it enables to characterize biological processes in space and time at the subcellular level. In fluorescence microscopy imaging, the moving tagged structures of interest, such as vesicles, appear as bright spots over a static or nonstatic background. In this paper, we consider the problem of vesicle segmentation and time-varying background estimation at the cellular scale. The main idea is to formulate the joint segmentation-estimation problem in the general conditional random field framework. Furthermore, segmentation of vesicles and background estimation are alternatively performed by energy minimization using a min cut-max flow algorithm. The proposed approach relies on a detection measure computed from intensity contrasts between neighboring blocks in fluorescence microscopy images. This approach permits analysis of either 2D + time or 3D + time data. We demonstrate the performance of the so-called C-CRAFT through an experimental comparison with the state-of-the-art methods in fluorescence video-microscopy. We also use this method to characterize the spatial and temporal distribution of Rab6 transport carriers at the cell periphery for two different specific adhesion geometries.
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http://dx.doi.org/10.1109/TIP.2014.2380178DOI Listing
February 2015

Ets2 in tumor fibroblasts promotes angiogenesis in breast cancer.

PLoS One 2013 16;8(8):e71533. Epub 2013 Aug 16.

Department of Molecular and Cellular Biochemistry, College of Medicine, The Ohio State University, Columbus, Ohio, United States of America.

Tumor fibroblasts are active partners in tumor progression, but the genes and pathways that mediate this collaboration are ill-defined. Previous work demonstrates that Ets2 function in stromal cells significantly contributes to breast tumor progression. Conditional mouse models were used to study the function of Ets2 in both mammary stromal fibroblasts and epithelial cells. Conditional inactivation of Ets2 in stromal fibroblasts in PyMT and ErbB2 driven tumors significantly reduced tumor growth, however deletion of Ets2 in epithelial cells in the PyMT model had no significant effect. Analysis of gene expression in fibroblasts revealed a tumor- and Ets2-dependent gene signature that was enriched in genes important for ECM remodeling, cell migration, and angiogenesis in both PyMT and ErbB2 driven-tumors. Consistent with these results, PyMT and ErbB2 tumors lacking Ets2 in fibroblasts had fewer functional blood vessels, and Ets2 in fibroblasts elicited changes in gene expression in tumor endothelial cells consistent with this phenotype. An in vivo angiogenesis assay revealed the ability of Ets2 in fibroblasts to promote blood vessel formation in the absence of tumor cells. Importantly, the Ets2-dependent gene expression signatures from both mouse models were able to distinguish human breast tumor stroma from normal stroma, and correlated with patient outcomes in two whole tumor breast cancer data sets. The data reveals a key function for Ets2 in tumor fibroblasts in signaling to endothelial cells to promote tumor angiogenesis. The results highlight the collaborative networks that orchestrate communication between stromal cells and tumor cells, and suggest that targeting tumor fibroblasts may be an effective strategy for developing novel anti-angiogenic therapies.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0071533PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3745457PMC
April 2014

Identifying survival associated morphological features of triple negative breast cancer using multiple datasets.

J Am Med Inform Assoc 2013 Jul-Aug;20(4):680-7. Epub 2013 Apr 12.

Department of Biomedical Informatics, The Ohio State University, Columbus, Ohio 43210, USA.

Background And Objective: Biomarkers for subtyping triple negative breast cancer (TNBC) are needed given the absence of responsive therapy and relatively poor prediction of survival. Morphology of cancer tissues is widely used in clinical practice for stratifying cancer patients, while genomic data are highly effective to classify cancer patients into subgroups. Thus integration of both morphological and genomic data is a promising approach in discovering new biomarkers for cancer outcome prediction. Here we propose a workflow for analyzing histopathological images and integrate them with genomic data for discovering biomarkers for TNBC.

Materials And Methods: We developed an image analysis workflow for extracting a large collection of morphological features and deployed the same on histological images from The Cancer Genome Atlas (TCGA) TNBC samples during the discovery phase (n=44). Strong correlations between salient morphological features and gene expression profiles from the same patients were identified. We then evaluated the same morphological features in predicting survival using a local TNBC cohort (n=143). We further tested the predictive power on patient prognosis of correlated gene clusters using two other public gene expression datasets.

Results And Conclusion: Using TCGA data, we identified 48 pairs of significantly correlated morphological features and gene clusters; four morphological features were able to separate the local cohort with significantly different survival outcomes. Gene clusters correlated with these four morphological features further proved to be effective in predicting patient survival using multiple public gene expression datasets. These results suggest the efficacy of our workflow and demonstrate that integrative analysis holds promise for discovering biomarkers of complex diseases.
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http://dx.doi.org/10.1136/amiajnl-2012-001538DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3721170PMC
September 2013

Canonical and atypical E2Fs regulate the mammalian endocycle.

Nat Cell Biol 2012 Nov 14;14(11):1192-202. Epub 2012 Oct 14.

Solid Tumor Biology Program, Department of Molecular Virology, Immunology and Medical Genetics, Department of Molecular Genetics, Comprehensive Cancer Center, The Ohio State University, Columbus, Ohio 43210, USA.

The endocycle is a variant cell cycle consisting of successive DNA synthesis and gap phases that yield highly polyploid cells. Although essential for metazoan development, relatively little is known about its control or physiologic role in mammals. Using lineage-specific cre mice we identified two opposing arms of the E2F program, one driven by canonical transcription activation (E2F1, E2F2 and E2F3) and the other by atypical repression (E2F7 and E2F8), that converge on the regulation of endocycles in vivo. Ablation of canonical activators in the two endocycling tissues of mammals, trophoblast giant cells in the placenta and hepatocytes in the liver, augmented genome ploidy, whereas ablation of atypical repressors diminished ploidy. These two antagonistic arms coordinate the expression of a unique G2/M transcriptional program that is critical for mitosis, karyokinesis and cytokinesis. These results provide in vivo evidence for a direct role of E2F family members in regulating non-traditional cell cycles in mammals.
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http://dx.doi.org/10.1038/ncb2595DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3616487PMC
November 2012

A signal processing approach for enriched region detection in RNA polymerase II ChIP-seq data.

BMC Bioinformatics 2012 Mar 13;13 Suppl 2:S2. Epub 2012 Mar 13.

College of Software, Nankai University, Tianjin, China.

Background: 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. However, since PolII enriched regions in the genome can be very long, existing peak finding algorithms for ChIP-seq data are not adequate for identifying such long regions.

Methods: Here we propose an enriched region detection method for ChIP-seq data to identify long enriched regions by combining a signal denoising algorithm with a false discovery rate (FDR) approach. The binned ChIP-seq data for PolII are first processed using a non-local means (NL-means) algorithm for purposes of denoising. Then, a FDR approach is developed to determine the threshold for marking enriched regions in the binned histogram.

Results: We first test our method using a public PolII ChIP-seq dataset and compare our results with published results obtained using the published algorithm HPeak. Our results show a high consistency with the published results (80-100%). Then, we apply our proposed method on PolII ChIP-seq data generated in our own study on the effects of hormone on the breast cancer cell line MCF7. The results demonstrate that our method can effectively identify long enriched regions in ChIP-seq datasets. Specifically, pertaining to MCF7 control samples we identified 5,911 segments with length of at least 4 Kbp (maximum 233,000 bp); and in MCF7 treated with E2 samples, we identified 6,200 such segments (maximum 325,000 bp).

Conclusions: We demonstrated the effectiveness of this method in studying binding patterns of PolII in cancer cells which enables further deep analysis in transcription regulation and epigenetics. Our method complements existing peak detection algorithms for ChIP-seq experiments.
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http://dx.doi.org/10.1186/1471-2105-13-S2-S2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3375632PMC
March 2012

Atypical E2F repressors and activators coordinate placental development.

Dev Cell 2012 Apr;22(4):849-62

Solid Tumor Biology Program, Department of Molecular Virology, Immunology and Medical Genetics, Human Cancer Genetics Program, Comprehensive Cancer Center, College of Medicine and Public Health, The Ohio State University, Columbus, OH 43210, USA.

The evolutionarily ancient arm of the E2f family of transcription factors consisting of the two atypical members E2f7 and E2f8 is essential for murine embryonic development. However, the critical tissues, cellular processes, and molecular pathways regulated by these two factors remain unknown. Using a series of fetal and placental lineage-specific cre mice, we show that E2F7/E2F8 functions in extraembryonic trophoblast lineages are both necessary and sufficient to carry fetuses to term. Expression profiling and biochemical approaches exposed the canonical E2F3a activator as a key family member that antagonizes E2F7/E2F8 functions. Remarkably, the concomitant loss of E2f3a normalized placental gene expression programs, corrected placental defects, and fostered the survival of E2f7/E2f8-deficient embryos to birth. In summary, we identified a placental transcriptional network tightly coordinated by activation and repression through two distinct arms of the E2F family that is essential for extraembryonic cell proliferation, placental development, and fetal viability.
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http://dx.doi.org/10.1016/j.devcel.2012.01.013DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3483796PMC
April 2012

Non-parametric population analysis of cellular phenotypes.

Med Image Comput Comput Assist Interv 2011 ;14(Pt 2):343-51

Dept. of Computer Science and Eng., The Ohio State University, USA.

Methods to quantify cellular-level phenotypic differences between genetic groups are a key tool in genomics research. In disease processes such as cancer, phenotypic changes at the cellular level frequently manifest in the modification of cell population profiles. These changes are hard to detect due the ambiguity in identifying distinct cell phenotypes within a population. We present a methodology which enables the detection of such changes by generating a phenotypic signature of cell populations in a data-derived feature-space. Further, this signature is used to estimate a model for the redistribution of phenotypes that was induced by the genetic change. Results are presented on an experiment involving deletion of a tumor-suppressor gene dominant in breast cancer, where the methodology is used to detect changes in nuclear morphology between control and knockout groups.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4295822PMC
http://dx.doi.org/10.1007/978-3-642-23629-7_42DOI Listing
November 2011

Identifying nuclear phenotypes using semi-supervised metric learning.

Inf Process Med Imaging 2011 ;22:398-410

Dept. of Computer Science and Engg., The Ohio State University, USA.

In systems-based approaches for studying processes such as cancer and development, identifying and characterizing individual cells within a tissue is the first step towards understanding the large-scale effects that emerge from the interactions between cells. To this end, nuclear morphology is an important phenotype to characterize the physiological and differentiated state of a cell. This study focuses on using nuclear morphology to identify cellular phenotypes in thick tissue sections imaged using 3D fluorescence microscopy. The limited label information, heterogeneous feature set describing a nucleus, and existence of subpopulations within cell-types makes this a difficult learning problem. To address these issues, a technique is presented to learn a distance metric from labeled data which is locally adaptive to account for heterogeneity in the data. Additionally, a label propagation technique is used to improve the quality of the learned metric by expanding the training set using unlabeled data. Results are presented on images of tumor stroma in breast cancer, where the framework is used to identify fibroblasts, macrophages and endothelial cells--three major stromal cells involved in carcinogenesis.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4285701PMC
http://dx.doi.org/10.1007/978-3-642-22092-0_33DOI Listing
August 2011

Patch-based Markov models for event detection in fluorescence bioimaging.

Med Image Comput Comput Assist Interv 2008 ;11(Pt 2):95-103

INRIA Rennes - Bretagne Atlantique, Campus de Beaulieu, F-35042 Rennes.

The study of protein dynamics is essential for understanding the multi-molecular complexes at subcellular levels. Fluorescent Protein (XFP)-tagging and time-lapse fluorescence microscopy enable to observe molecular dynamics and interactions in live cells, unraveling the live states of the matter. Original image analysis methods are then required to process challenging 2D or 3D image sequences. Recently, tracking methods that estimate the whole trajectories of moving objects have been successfully developed. In this paper, we address rather the detection of meaningful events in spatio-temporal fluorescence image sequences, such as apparent stable "stocking areas" involved in membrane transport. We propose an original patch-based Markov modeling to detect spatial irregularities in fluorescence images with low false alarm rates. This approach has been developed for real image sequences of cells expressing XFP-tagged Rab proteins, known to regulate membrane trafficking.
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http://dx.doi.org/10.1007/978-3-540-85990-1_12DOI Listing
December 2008