Academic literature on the topic 'Cellular atlas'
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Journal articles on the topic "Cellular atlas"
Hill, Matthew C., Zachary A. Kadow, Lele Li, Tien T. Tran, Joshua D. Wythe, and James F. Martin. "A cellular atlas of Pitx2-dependent cardiac development." Development 146, no. 12 (June 14, 2019): dev180398. http://dx.doi.org/10.1242/dev.180398.
Full textSrivastava, Sudhir, Paul D. Wagner, Shannon K. Hughes, and Sharmistha Ghosh. "PreCancer Atlas: Present and Future." Cancer Prevention Research 16, no. 7 (July 5, 2023): 379–84. http://dx.doi.org/10.1158/1940-6207.capr-22-0435.
Full textMcCampbell, Kristen K., Kristin N. Springer, and Rebecca A. Wingert. "Atlas of Cellular Dynamics during Zebrafish Adult Kidney Regeneration." Stem Cells International 2015 (2015): 1–19. http://dx.doi.org/10.1155/2015/547636.
Full textKunst, Michael, Eva Laurell, Nouwar Mokayes, Anna Kramer, Fumi Kubo, António M. Fernandes, Dominique Förster, Marco Dal Maschio, and Herwig Baier. "A Cellular-Resolution Atlas of the Larval Zebrafish Brain." Neuron 103, no. 1 (July 2019): 21–38. http://dx.doi.org/10.1016/j.neuron.2019.04.034.
Full textDing, Song‐Lin, Joshua J. Royall, Susan M. Sunkin, Lydia Ng, Benjamin A. C. Facer, Phil Lesnar, Angie Guillozet‐Bongaarts, et al. "Comprehensive cellular‐resolution atlas of the adult human brain." Journal of Comparative Neurology 524, no. 16 (September 15, 2016): 3127–481. http://dx.doi.org/10.1002/cne.24080.
Full textDing, Song-Lin, Joshua J. Royall, Susan M. Sunkin, Lydia Ng, Benjamin A. C. Facer, Phil Lesnar, Angie Guillozet-Bongaarts, et al. "Comprehensive cellular-resolution atlas of the adult human brain." Journal of Comparative Neurology 524, no. 16 (September 15, 2016): Spc1. http://dx.doi.org/10.1002/cne.24097.
Full textDing, Song-Lin, Joshua J. Royall, Susan M. Sunkin, Lydia Ng, Benjamin A. C. Facer, Phil Lesnar, Angie Guillozet-Bongaarts, et al. "Comprehensive cellular-resolution atlas of the adult human brain." Journal of Comparative Neurology 525, no. 2 (December 5, 2016): 407. http://dx.doi.org/10.1002/cne.24130.
Full textGÁL, V., J. HÁMORI, T. ROSKA, D. BÁLYA, ZS BOROSTYÁNKŐI, M. BRENDEL, K. LOTZ, et al. "RECEPTIVE FIELD ATLAS AND RELATED CNN MODELS." International Journal of Bifurcation and Chaos 14, no. 02 (February 2004): 551–84. http://dx.doi.org/10.1142/s0218127404009545.
Full textKHAW, P. T. "Atlas of Glaucoma." British Journal of Ophthalmology 83, no. 8 (August 1, 1999): 994d. http://dx.doi.org/10.1136/bjo.83.8.994d.
Full textFfytche, T. J. "Atlas der Kontaktlinsenanpassung." British Journal of Ophthalmology 70, no. 1 (January 1, 1986): 80. http://dx.doi.org/10.1136/bjo.70.1.80.
Full textDissertations / Theses on the topic "Cellular atlas"
Collin, Antoine. "Annotation cellulaire automatique pour la construction d'un atlas cellulaire." Electronic Thesis or Diss., Université Côte d'Azur, 2024. http://www.theses.fr/2024COAZ6039.
Full textSingle-cell gene expression analysis technologies, which have emerged over the last ten years, are profoundly changing approaches to cell biology. The analysis of single-cell data is a complex process involving many steps. A key step is cell annotation, which involves assigning the most relevant cell type to the different cells analysed. Correct cell annotation determines the quality of subsequent analyses. This complex task requires biological expertise of the tissue of interest and computational expertise to carry out data analysis. Initiatives such as the HCA provide large reference atlases with curated annotation. As such, they represent an opportunity to develop deep learning models capable of automating the annotation process.The aim of this thesis was to set up automatic annotation tools that could operate on large datasets. To achieve this, two lines of work were developed: first, I created an atlas of the human airways comprising more than 400,000 cells based on several dozen biopsies obtained from patients with early forms of chronic obstructive pulmonary disease (COPD), which were compared with as many biopsies from healthy volunteers of the same age. I then developed an automatic annotation method after reviewing the state of the art existing tools.In the first part, I was able to characterise the central role played by cigarette smoke, mainly in the epithelial cells located on the surface of the tracheobronchial airways, and thus directly exposed to cigarette smoke. The populations affected are characterised by the expression of genes coding for detoxification enzymes or enzymes involved in xenobiotic metabolism. None of these genes were affected in either ex-smokers or healthy patients. There appears to be a reversibility of the pathology following cessation of smoking, despite the molecular changes induced during initial exposure to cigarette smoke. My work is now currently extended by spatial transcriptomic approaches and analysis of the expression of different transcript isoforms.In the second part, I explored existing automatic annotation methods in the light of the knowledge acquired when annotating the COPD atlas. I began with an extensive review of the literature, with a particular interest in methods using deep learning models. I then developed an automatic annotation tool, scMusketeers, whose architecture favours the construction of a latent space reinforcing cell type while minimising experimental inter-batch effects. It compared favorably to 7 currently available tools on 12 different datasets, particularly in the task of detecting rare cell types
Deprez, Marie. "Étude de l’hétérogénéité cellulaire et des dynamiques de régénération de l’épithélium respiratoire sain par analyses des signatures transcriptionnelles sur cellules uniques." Electronic Thesis or Diss., Université Côte d'Azur (ComUE), 2019. http://www.theses.fr/2019AZUR6022.
Full textImprovements made in nucleic acid sequencing and cell handling technologies now offer the opportunity to analyze simultaneously the content of numerous single cells (RNA, DNA, ...) by global and unbiased approaches. This single-cell ‘omics’ revolution provides a new framework to revisit the “Cell Theory”, elaborated over several centuries, and essentially based on morphological and functional features. The many cell modalities now accessible at single- cell level, such as their transcriptome, spatial localization, developmental trajectories, enrich considerably this definition, and set a renewed context to precisely reassess the definition of ‘cell types’, ‘cell states’ as well as their different interactions and fates.My thesis work initially set up ad hoc approaches and statistical framework to analyze appropriately these single-cell data, which deeply differ from standard bulk RNA-seq. High variance, presence of a huge percentage of null values, large volume of data are among the specific characteristics of these datasets. My work was centered on the main experimental model of my host laboratory, e.g. the human airway epithelium. Human airways are lined by a pseudostratified epithelium mainly composed of basal, secretory, goblet and multiciliated cells. Airways also constitute a true cellular ecosystem, in which the epithelial layer interacts closely with immune and mesenchymal cells. This coordination between cells ensures proper defense of the respiratory system and its correct regeneration in case of external aggression and injuries. A better understanding of the operating sequences in normal and physiopathological situations is relevant in pathologies such as chronic obstructive pulmonary disease, asthma or cystic fibrosis.First, I characterized at a single cell level the precise and cell-specific sequence of events leading to functional regeneration of the epithelium, using a 3D model of human cells. I then built a single-cell atlas of the different cell types that are lining healthy human airways from the nose to the 12th generation of bronchi.By applying computational and statistical approaches, I have identified cell lineage hierarchies and was able to reconstruct a comprehensive cell trajectory roadmap in human airways. I not only confirmed previously described cell lineages, but I have also discovered a novel trajectory that links goblet cells to multiciliated cells, identifying novel cell populations and molecular interactors involved in the process of healthy human airway epithelium regeneration. The profiling of 12 healthy volunteers then generated a dataset of 77,969 cells, derived from 35 distinct locations. The resulting atlas is composed of more than 26 epithelial, immune and stromal cell types demonstrating the cellular heterogeneity present in the airways. Its analysis has revealed a strong proximo-distal gradient of expression in suprabasal, secretory, or multiciliated cells between the nose and lung airways. My work has also improved the characterization of rare cells, including “hillock” cells that have been previously described in mice.In conclusion, this work probably represents one of the first single-cell investigations in human airways. It brings original contributions to our understanding of differentiation’s dynamics and cellular heterogeneity in healthy human airways. The resulting resource will be extremely useful for any future single-cell investigators and also for establishing a very useful joint between clinical and biological works. As such, it will constitute a reference in any future project aiming to precisely analyze specific disease conditions
Tondeur, Sylvie. "Cellule souches hématopoïétiques et cellules souches embryonnaires humaines : analyse du transcriptome et mise en ligne des données par la création d'un atlas d'expression." Montpellier 1, 2009. http://www.theses.fr/2009MON1T012.
Full textDNA-microarray based transcriptome study can monitor the expression of a whole genome in one experiment and has completely changed our manner to conceive biological questions. We applied this technology to the study of stem cells. The transcriptome analysis of human embryonic stem cells (hESC), a main model of pluripotent stem cells, led us to better define molecular mechanisms of pluripotency. Of note we compared hESC to human oocytes in order to identify intinsic determinants of pluripotency. Affymetrix Exon ST 1. 0 microarrays are high resolution platforms that can measure the expression of all the exons of a genome. We used this new microarray to map exonic expression profile (exome) of hematopoietic stem cells and mature blood cells. Our work showed hematopoietic specific alternative splicing events (NEDD9, CD74) and an alternative switch for some transcripts during maturation (INPP4B, PTPLA, CXCL3, COMMD6). Alternatively spliced genes are notably involved in cell motility and immune response. Finally, we created a web atlas, Amazonia! (http://amazonia. Transcriptome. Eu/), for an easy access to public transciptome data. Gene expression profiles can be visualised as histograms or colored matrixes in more than 5,000 samples regrouped in thematic pages such as «stem cell», «hematology» or «exon»
Fougeron, Denis. "Etude et mise en oeuvre de cellules résistantes aux radiations dans le cadre de l'évolution du détecteur à pixels d'Atlas technologie CMOS 65 nm." Electronic Thesis or Diss., Toulon, 2020. http://www.theses.fr/2020TOUL0005.
Full textThis study is inside an international collaboration context, RD53, which its goal is to provide to the scientific community an electronic front-end for the readout of the future pixel detector in 2022. The 65 nm technology chosen by the collaboration will have to be operational in a highly radioactive environment (10 MGray) for five years without maintenance operation.Two experimental approaches are described in this thesis: 1. Irradiation studies were carried out to estimate the dose tolerance (TID) of the 65 nm process to fix all essentials design rules for digital and analog cells implanted in the final circuit. Test vehicles (PCM) were defined for irradiation using an X-ray source (10 keV - 3 kW) to estimate dose effects. The results we obtained are summarized in the document. 2. In order to optimize the tolerance of memories to the SEE effects, several ASIC prototypes havebeen designed. These prototypes include different architectures for irradiation characterization. Several irradiation campaigns have been carried out using a heavy ion beam and a proton beam in order to a cross-section as accurate as possible
Books on the topic "Cellular atlas"
Butler, E. B. Cytology of bodycavity fluids: A colour atlas. London: Chapman and Hall, 1986.
Find full textButler, E. B. Cytology of body cavity fluids: A colour atlas. London: Chapman and Hall, 1986.
Find full textKini, Sudha R. Color atlas of differential diagnosis in exfoliative and aspiration cytopathology. 2nd ed. Philadelphia: Wolters Kluwer/Lippincott Williams & Wilkins, 2011.
Find full textJunqueira, Luiz Carlos Uchôa, 1920- and Carneiro José, eds. Basic histology: Text & atlas. New York: Lange Medical Books, McGraw-Hill, Medical Pub. Division, 2003.
Find full textWuensche, Andrew. The global dynamics of cellular automata: An atlas of basin of attraction fields of one-dimensional cellular automata. Reading, Mass: Addison-Wesley, 1992.
Find full text1928-, Boddington Michael M., ed. Atlas of serous fluid cytopathology: A guide to the cells of pleural, pericardial, peritoneal, and hydrocele fluids. Dordrecht: Kluwer Academic Publishers, 1989.
Find full textGabrijela, Kocjan, ed. Clinical cytopathology of the head and neck: A text and atlas. London: Greenwich Medical Media, 2001.
Find full textLearmonth, Geneviève Warner. An atlas of cytopathology of the head and neck: With clinical and histological correlations. London: Arnold, 1998.
Find full textJean-Claude, Roland, ed. Atlas de biologie cellulaire. 4th ed. Paris: Masson, 1993.
Find full textAckermann, Hans-Wolfgang. Viral pathogenesis in diagrams. Boca Raton, Fla: CRC Press, 2001.
Find full textBook chapters on the topic "Cellular atlas"
Anderson, Janice R. "General Cellular Reactions." In Atlas of Skeletal Muscle Pathology, 19–25. Dordrecht: Springer Netherlands, 1985. http://dx.doi.org/10.1007/978-94-009-4866-2_2.
Full textSpanel-Borowski, Katharina. "The Cortex and Cellular Stromatolysis." In Atlas of the Mammalian Ovary, 31–37. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-30535-1_4.
Full textKatz, Arnold M. "Molecular and Cellular Basis of Contraction." In Atlas of Heart Failure, 1–17. London: Current Medicine Group, 2002. http://dx.doi.org/10.1007/978-1-4615-6490-4_1.
Full textKatz, Arnold M. "Molecular and Cellular Basis of Contraction and Relaxation." In Atlas of HEART FAILURE, 1–14. London: Current Medicine Group, 2005. http://dx.doi.org/10.1007/978-1-4757-4558-0_1.
Full textRomanò, Massimo. "General Principles of Anatomy and Cellular Electrophysiology." In Text Atlas of Practical Electrocardiography, 1–5. Milano: Springer Milan, 2015. http://dx.doi.org/10.1007/978-88-470-5741-8_1.
Full textSawyer, Douglas B., and Wilson S. Colucci. "Molecular and Cellular Events in Myocardial Hypertrophy and Failure." In Atlas of HEART FAILURE, 61–81. London: Current Medicine Group, 2005. http://dx.doi.org/10.1007/978-1-4757-4558-0_4.
Full textSawyer, Douglas B., and Wilson S. Colucci. "Molecular and Cellular Events in Myocardial Hypertrophy and Failure." In Atlas of Heart Failure, 65–85. London: Current Medicine Group, 2002. http://dx.doi.org/10.1007/978-1-4615-6490-4_4.
Full textPaoli, Donatella, Francesco Lombardo, and Andrea Lenzi. "Image Gallery: Non-Sperm Cellular Components (Figs. 124–150)." In Atlas of Human Semen Examination, 79–92. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-39998-6_4.
Full textFrühwirth, Rudolf, and Are Strandlie. "Track Finding." In Pattern Recognition, Tracking and Vertex Reconstruction in Particle Detectors, 81–102. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-65771-0_5.
Full textLegdou, Anass, Hassan Chafik, Aouatif Amine, Said Lahssini, and Mohamed Berrada. "A Random Forest-Cellular Automata Modeling Approach to Predict Future Forest Cover Change in Middle Atlas Morocco, Under Anthropic, Biotic and Abiotic Parameters." In Lecture Notes in Computer Science, 91–100. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-51935-3_10.
Full textConference papers on the topic "Cellular atlas"
Link, Jason M., Brittany Allen-Petersen, Andrew Gunderson, Danielle Jorgens, Craig Dorrell, Jody Hooper, Philip Streeter, et al. "Abstract B118: Developing a molecular and cellular atlas of pancreatic disease." In Abstracts: AACR Special Conference on Pancreatic Cancer: Innovations in Research and Treatment; May 18-21, 2014; New Orleans, LA. American Association for Cancer Research, 2015. http://dx.doi.org/10.1158/1538-7445.panca2014-b118.
Full textPeters, H., P. Potla, J. Rockel, T. Tockovska, K. Delos Santos, S. Vohra, C. Pastrello, et al. "POS0213 INFRAPATELLAR FAT PAD IN KNEE OSTEOARTHRITIS: CELLULAR AND TRANSCRIPTOMIC ATLAS." In EULAR 2024 European Congress of Rheumatology, 12-15 June. Vienna, Austria. BMJ Publishing Group Ltd and European League Against Rheumatism, 2024. http://dx.doi.org/10.1136/annrheumdis-2024-eular.5719.
Full textWu, Sunny Z., Daniel Roden, Ghamdan Al Eryani, Simon Junankar, Elgene Lim, Aatish Thennavan, Alma Andersson, et al. "Abstract 129: An integrated multi-omic cellular atlas of human breast cancers." In Proceedings: AACR Annual Meeting 2021; April 10-15, 2021 and May 17-21, 2021; Philadelphia, PA. American Association for Cancer Research, 2021. http://dx.doi.org/10.1158/1538-7445.am2021-129.
Full textSelka, F., T. Blein, J. Burguet, E. Biot, P. Laufs, and P. Andrey. "Towards a Spatio-Temporal Atlas of 3D Cellular Parameters During Leaf Morphogenesis." In 2017 IEEE International Conference on Computer Vision Workshop (ICCVW). IEEE, 2017. http://dx.doi.org/10.1109/iccvw.2017.14.
Full textLuca, Bogdan A., Chloé B. Steen, Armon Azizi, Magdalena Matusiak, Joanna Przybyl, Nastaran Neishaboori, Almudena Espín Pérez, et al. "Abstract 3443: Atlas of clinically-distinct cell states and cellular ecosystems across human solid tumors." In Proceedings: AACR Annual Meeting 2020; April 27-28, 2020 and June 22-24, 2020; Philadelphia, PA. American Association for Cancer Research, 2020. http://dx.doi.org/10.1158/1538-7445.am2020-3443.
Full textKaur, G., A. Tjitropranoto, Q. Wang, S. B. Shaikh, and I. Rahman. "Lung Cellular Senescence Atlas by Single Cell RNA Sequencing and Other Biomarkers in Patients With COPD." In American Thoracic Society 2023 International Conference, May 19-24, 2023 - Washington, DC. American Thoracic Society, 2023. http://dx.doi.org/10.1164/ajrccm-conference.2023.207.1_meetingabstracts.a2661.
Full textTesta, Stefano, Aastha Pal, Ajay Subramanian, Minggui Pan, Nam Bui, Sushama Varma, Matt van de Rijn, Kristen Ganjoo, Anusha Kalbasi, and Everett J. Moding. "325 CellSARCTx: a single-cell transcriptomics atlas of adoptive cellular therapy targets in soft tissue sarcomas." In SITC 39th Annual Meeting (SITC 2024) Abstracts, A376—A378. BMJ Publishing Group Ltd, 2024. http://dx.doi.org/10.1136/jitc-2024-sitc2024.0325.
Full textHines, William C., Kate Thi, Maria Rojec, Gaelen Stanford-Moore, and Mina J. Bissell. "Abstract B86: A cytometric atlas of the human breast: Comprehensive characterization reveals 12 distinct cell populations." In Abstracts: AACR Special Conference on Cellular Heterogeneity in the Tumor Microenvironment; February 26 — March 1, 2014; San Diego, CA. American Association for Cancer Research, 2015. http://dx.doi.org/10.1158/1538-7445.chtme14-b86.
Full textFowlkes, C. C., C. L. Luengo Hendriks, S. V. E. Keranen, M. D. Biggin, D. W. Knowles, D. Sudar, and J. Malik. "Registering Drosophila embryos at cellular resolution to build a quantitative 3D atlas of gene expression patterns and morphology." In 2005 IEEE Computational Systems Bioinformatics Conference Workshops and Poster Abstracts. IEEE, 2005. http://dx.doi.org/10.1109/csbw.2005.118.
Full textGay, A. C., M. Banchero, A. K. Saikumar Jayalatha, M. Berg, T. E. Gillett, B. H. Ly, P. Van Der Velde, et al. "A single-cell atlas of the airway wall in patients with asthma reveals novel cellular mechanisms of disease." In ERS Lung Science Conference 2024 abstracts. European Respiratory Society, 2024. http://dx.doi.org/10.1183/23120541.lsc-2024.275.
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