Gotowa bibliografia na temat „Tissue microarray”
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Artykuły w czasopismach na temat "Tissue microarray"
Yang, Jun, Mingjuan Zhang, Baoshan Su, XiaoLi Chen i AnJing Kang. "A novel tissue microarray instrumentation:The HT-1 tissue microarrayer". Indian Journal of Pathology and Microbiology 55, nr 3 (2012): 314. http://dx.doi.org/10.4103/0377-4929.101736.
Pełny tekst źródłaBarrette, Kathleen, Joost J. van den Oord i Marjan Garmyn. "Tissue Microarray". Journal of Investigative Dermatology 134, nr 9 (wrzesień 2014): 1–4. http://dx.doi.org/10.1038/jid.2014.277.
Pełny tekst źródłaRoszkowiak, Lukasz, i Carlos Lopez. "PATMA: parser of archival tissue microarray". PeerJ 4 (1.12.2016): e2741. http://dx.doi.org/10.7717/peerj.2741.
Pełny tekst źródłaKaur, Rashmeet, Nagaraja A, Richa Bansal, Sujata Saxena i Bhavana Rai. "Tissue microarray- A review". International Journal of Oral Health Dentistry 4, nr 3 (15.10.2018): 152–55. http://dx.doi.org/10.18231/2395-499x.2018.0035.
Pełny tekst źródłaKim, Woo Ho. "High-Density Tissue Microarray". American Journal of Surgical Pathology 26, nr 9 (wrzesień 2002): 1236–37. http://dx.doi.org/10.1097/00000478-200209000-00017.
Pełny tekst źródłaRubin, Mark A., i Rodney L. Dunn. "High-Density Tissue Microarray". American Journal of Surgical Pathology 26, nr 9 (wrzesień 2002): 1237–38. http://dx.doi.org/10.1097/00000478-200209000-00018.
Pełny tekst źródłaPage, Robert N., Roy King i Paul B. Googe. "Tissue Microarray in Melanoma". Journal of Histotechnology 26, nr 4 (grudzień 2003): 271–74. http://dx.doi.org/10.1179/his.2003.26.4.271.
Pełny tekst źródłaPackeisen, J. "Demystified ... Tissue microarray technology". Molecular Pathology 56, nr 4 (1.08.2003): 198–204. http://dx.doi.org/10.1136/mp.56.4.198.
Pełny tekst źródłaJiang, Hui-Yong, Xue-Feng Zhang, Li Liu, Hui-Ling Li i Tong Zhao. "A novel tissue array technique for high-throughput tissue microarray analysis — microarray groups". In Vitro Cellular & Developmental Biology - Animal 43, nr 3-4 (21.05.2007): 109–12. http://dx.doi.org/10.1007/s11626-007-9019-3.
Pełny tekst źródłaRangel, Catherine Starrs. "The Tissue Microarray: Helpful Hints!" Journal of Histotechnology 25, nr 2 (czerwiec 2002): 93–100. http://dx.doi.org/10.1179/his.2002.25.2.93.
Pełny tekst źródłaRozprawy doktorskie na temat "Tissue microarray"
Amaral, Telmo. "Analysis of breast tissue microarray spots". Thesis, University of Dundee, 2010. https://discovery.dundee.ac.uk/en/studentTheses/0a83915d-2f11-4b89-9c24-8dc3c15346f2.
Pełny tekst źródłaNguyễn, Hoài Nam. "Méthodes et algorithmes de segmentation et déconvolution d'images pour l'analyse quantitative de Tissue Microarrays". Thesis, Rennes 1, 2017. http://www.theses.fr/2017REN1S104/document.
Pełny tekst źródłaThis thesis aims at developing dedicated methods for quantitative analysis of Tissue Microarray (TMA) images acquired by fluorescence scanners. We addressed there issues in biomedical image processing, including segmentation of objects of interest (i.e. tissue samples), correction of acquisition artifacts during scanning process and improvement of acquired image resolution while taking into account imaging modality and scanner design. The developed algorithms allow to envisage a novel automated platform for TMA analysis, which is highly required in cancer research nowadays. On a TMA slide, multiple tissue samples which are collected from different donors are assembled according to a grid structure to facilitate their identification. In order to establish the link between each sample and its corresponding clinical data, we are not only interested in the localization of these samples but also in the computation of their array (row and column) coordinates according to the design grid because the latter is often very deformed during the manufacturing of TMA slides. However, instead of directly computing array coordinates as existing approach, we proposed to reformulate this problem as the approximation of the deformation of the theoretical TMA grid using “thin plate splines” given the result of tissue sample localization. We combined a wavelet-based detection and a ellipse-based segmentation to eliminate false alarms and thus improving the localization result of tissue samples. According to the scanner design, images are acquired pixel by pixel along each line, with a change of scan direction between two subsequent lines. Such scanning system often suffers from pixel mis-positioning (jitter) due to imperfect synchronization of mechanical and electronic components. To correct these scanning artifacts, we proposed a variational method based on the estimation of pixel displacements on subsequent lines. This method, inspired from optical flow methods, consists in estimating a dense displacement field by minimizing an energy function composed of a nonconvex data fidelity term and a convex regularization term. We used half-quadratic splitting technique to decouple the original problem into two small sub-problems: one is convex and can be solved by standard optimization algorithm, the other is non-convex but can be solved by a complete search. To improve the resolution of acquired fluorescence images, we introduced a method of image deconvolution by considering a family of convex regularizers. The considered regularizers are generalized from the concept of Sparse Variation which combines the L1 norm and Total Variation (TV) to favors the co-localization of high-intensity pixels and high-magnitude gradient. The experiments showed that the proposed regularization approach produces competitive deconvolution results on fluorescence images, compared to those obtained with other approaches such as TV or the Schatten norm of Hessian matrix
Sievertzon, Maria. "Transcript profiling of small tissue samples using microarray technology". Doctoral thesis, Stockholm Department of Biotechnology, Royal Institute of Technology, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-158.
Pełny tekst źródłaCheng, Yabin. "Tissue microarray based biomarker study in human cutaneous melanoma". Thesis, University of British Columbia, 2014. http://hdl.handle.net/2429/46655.
Pełny tekst źródłaXie, Dan, i 謝丹. "Application of high-throughput tissue microarray technology in cancer research". Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2004. http://hub.hku.hk/bib/B30283619.
Pełny tekst źródłaMckenzie, Gavin Medical Sciences Faculty of Medicine UNSW. "The analysis of signalling pathways in sporadic colorectal carcinoma using tissue microarrays". Publisher:University of New South Wales. Medical Sciences, 2008. http://handle.unsw.edu.au/1959.4/43370.
Pełny tekst źródłaJernås, Margareta. "Microarray analysis of gene expression in human adipocytes and adipose tissue /". Göteborg : Institute of Medicine, Dept. of Molecular and Clinical Medicine, Sahlgrenska Academy, Göteborg University, 2008. http://hdl.handle.net/2077/9583.
Pełny tekst źródłaPANSINI, P. F. "Potencial Prognóstico da Survivina em Carcinoma Epidermóide da Cavidade Bucal". Universidade Federal do Espírito Santo, 2017. http://repositorio.ufes.br/handle/10/7104.
Pełny tekst źródłaO carcinoma epidermóide de cabeça e pescoço (CECP) é o sexto tipo de câncer mais comum em todo o mundo. Nos últimos anos, tem sido sugerida a participação da survivina na progressão tumoral em CECP. Este estudo teve como objetivo avaliar a survivina como potencial biomarcador de progressão tumoral em CECB. Foram utilizados no estudo dados clínicos e amostras biológicas de 115 indivíduos com carcinoma epidermóide da cavidade bucal. Lâminas contendo tecidos tumorais coradas pelo método hematoxilina e eosina foram usadas para as análises histopatológicas para avaliar o infiltrado linfocitário tumoral, padrão de invasão tumoral, gradação tumoral, invasão vascular, linfática e perineural. Tissue Microarrays foram construídos para realizar a análise imunohistoquímica da expressão da proteína survivina utilizando o anticorpo primário monoclonal de coelho anti-survivina. Para avaliar as associações entre as variáveis estudadas foram utilizados os testes Qui-Quadrado e o Exato de Fisher. A comparação das médias dos segmentos foi obtida pelo teste T de amostras independentes. As curvas de sobrevida foram calculadas pelo modelo de Kaplan-Meier e confirmadas pelo modelo multivariado de Cox. Nossos resultados mostraram existir correlação entre o infiltrado linfocitário tumoral alto, tamanho do tumor primário T1/T2 (p = 0,001) e estadiamento clínico I e II (p = 0,005). O padrão de invasão tumoral tipo IV foi correlacionado com o tamanho do tumor primário T3/T4 (p = 0,006) e estadiamento clínico avançado (estádio III e IV) (p = 0,028). Invasão perineural foi associada com o tamanho do tumor primário T1/T2 (p = 0,035). A expressão nuclear da survivina na porção mediana do tumor mostrou associação com a metástase em linfonodos regionais (p = 0,004) e o estadiamento clínico (p = 0,041). A análise regressiva multivariada confirmou que as variáveis tamanho do tumor primário (p = 0,004) e acometimento linfonodal (p= 0,06) são fatores prognósticos independentes para sobrevida global, enquanto o etilismo influencia na sobrevida livre de doença (p = 0,048). Com este estudo pode-se concluir que a elevada expressão da survivina está correlacionada com o comportamento tumoral mais agressivo, estadiamento clínico avançado, presença de mestástase linfonodal, podendo ser considerada como indicador de prognóstico em pacientes com CECB. A variável histopatológica padrão de invasão tumoral mostrou que sua correlação com tamanho do tumor primário e estadiamento clínico avançado podendo estar relacionada ao pior prognóstico dos pacientes em CECB.
Foster, Cheryl June. "Identifying a prognostic test in follicular lymphoma using a tissue microarray and immunohistochemistry". Thesis, Kingston, Ont. : [s.n.], 2008. http://hdl.handle.net/1974/1296.
Pełny tekst źródłaHabibi, Golareh. "Y-box binding protein-1 (YB-1) is a bio-marker of aggressiveness in breast cancer and is a potential target for therapeutic intervention". Thesis, University of British Columbia, 2008. http://hdl.handle.net/2429/911.
Pełny tekst źródłaKsiążki na temat "Tissue microarray"
-S, Liu Brian C., i Ehrlich Joshua R, red. Tissue proteomics: Pathways, biomarkers, and drug discovery. Totowa, N.J: Humana Press, 2008.
Znajdź pełny tekst źródłaSimon, Ronald, red. Tissue Microarrays. Totowa, NJ: Humana Press, 2010. http://dx.doi.org/10.1007/978-1-60761-806-5.
Pełny tekst źródłaTissue microarrays: Methods and protocols. New York, N.Y: Humana Press, 2010.
Znajdź pełny tekst źródłaEhrlich, Joshua R., i Brian Liu. Tissue Proteomics: Pathways, Biomarkers, and Drug Discovery. Humana Press, 2010.
Znajdź pełny tekst źródłaTissue proteomics: Pathways, biomarkers, and drug discovery. Totowa, N.J: Humana Press, 2008.
Znajdź pełny tekst źródłaTissue Proteomics: Pathways, Biomarkers, and Drug Discovery (Methods in Molecular Biology). Humana Press, 2008.
Znajdź pełny tekst źródłaSimon, Ronald. Tissue Microarrays: Methods and Protocols. Humana Press, 2016.
Znajdź pełny tekst źródłaHewitt, Stephen M. Tissue Microarrays: Methods and Applications (Methods in Molecular Biology). Humana Press, 2007.
Znajdź pełny tekst źródłaZrazhevskiy, P., i X. Gao. Bioconjugated quantum dots for tumor molecular imaging and profiling. Redaktorzy A. V. Narlikar i Y. Y. Fu. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780199533060.013.17.
Pełny tekst źródłaCzęści książek na temat "Tissue microarray"
Wilkerson, Myra L., i Stephen M. Hewitt. "Tissue Microarray". W Handbook of Practical Immunohistochemistry, 105–17. New York, NY: Springer New York, 2015. http://dx.doi.org/10.1007/978-1-4939-1578-1_10.
Pełny tekst źródłaWilkerson, Myra L., i Stephen Hewitt. "Tissue Microarray". W Handbook of Practical Immunohistochemistry, 161–72. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-83328-2_11.
Pełny tekst źródłaWilkerson, Myra, i Erin Powell. "Tissue Microarray". W Handbook of Practical Immunohistochemistry, 45–54. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-8062-5_6.
Pełny tekst źródłaFaoro, Valentina, i Anna Sapino. "Tissue Microarray (TMA)". W Guidelines for Molecular Analysis in Archive Tissues, 23–26. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-17890-0_5.
Pełny tekst źródłaKoo, Matthew, Jill M. Squires, Daphne Ying i Jiaoti Huang. "Making a Tissue Microarray". W Methods in Molecular Biology, 313–23. New York, NY: Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4939-8935-5_27.
Pełny tekst źródłaKorenberg, Michael J., Pedro Farinha i Randy D. Gascoyne. "Predicting Survival in Follicular Lymphoma Using Tissue Microarrays". W Microarray Data Analysis, 255–68. Totowa, NJ: Humana Press, 2007. http://dx.doi.org/10.1007/978-1-59745-390-5_16.
Pełny tekst źródłaSimon, Ronald. "Applications of Tissue Microarray Technology". W Methods in Molecular Biology, 1–16. Totowa, NJ: Humana Press, 2010. http://dx.doi.org/10.1007/978-1-60761-806-5_1.
Pełny tekst źródłaGaudreau, Pierre-Olivier, Isabelle Cousineau i John Stagg. "Optimal CCN4 Immunofluorescence for Tissue Microarray". W Methods in Molecular Biology, 13–21. New York, NY: Springer US, 2022. http://dx.doi.org/10.1007/978-1-0716-2744-0_2.
Pełny tekst źródłaSaremi, Nassim, i Alfred K. Lam. "Application of Tissue Microarray in Esophageal Adenocarcinoma". W Methods in Molecular Biology, 105–18. New York, NY: Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4939-7734-5_10.
Pełny tekst źródłaHu, Zhongting, Elbert Chang i Melissa Hodeib. "An Alternative Technology to Prepare Tissue Microarray Using Frozen Tissue Samples". W Methods in Molecular Biology, 81–91. Totowa, NJ: Humana Press, 2010. http://dx.doi.org/10.1007/978-1-60761-806-5_9.
Pełny tekst źródłaStreszczenia konferencji na temat "Tissue microarray"
Can, Ali, Musodiq O. Bello i Michael J. Gerdes. "Quantification of Subcellular Molecules in Tissue Microarray". W 2010 20th International Conference on Pattern Recognition (ICPR). IEEE, 2010. http://dx.doi.org/10.1109/icpr.2010.624.
Pełny tekst źródłaWu, Jiahua, Junyu Dong i Huiyu Zhou. "Image quantification of high-throughput tissue microarray". W Medical Imaging, redaktorzy Armando Manduca i Amir A. Amini. SPIE, 2006. http://dx.doi.org/10.1117/12.653564.
Pełny tekst źródłaAmaral, T., S. McKenna, K. Robertson i A. Thompson. "Automated classification of breast tissue microarray spots." W CTRC-AACR San Antonio Breast Cancer Symposium: 2008 Abstracts. American Association for Cancer Research, 2009. http://dx.doi.org/10.1158/0008-5472.sabcs-4010.
Pełny tekst źródłaXing, Fuyong, Baiyang Liu, Xin Qi, David J. Foran i Lin Yang. "Digitized tissue microarray classification using sparse reconstruction". W SPIE Medical Imaging, redaktorzy David R. Haynor i Sébastien Ourselin. SPIE, 2012. http://dx.doi.org/10.1117/12.911900.
Pełny tekst źródłaCline, Harvey E., Ali Can i Dirk Padfield. "Segmentation of prostate cancer tissue microarray images". W Biomedical Optics 2006, redaktorzy Daniel L. Farkas, Dan V. Nicolau i Robert C. Leif. SPIE, 2006. http://dx.doi.org/10.1117/12.643180.
Pełny tekst źródłaGalizia, Antonella, Federica Viti, Alessandro Orro, Daniele D'Agostino, Ivan Merelli, Luciano Milanesi i Andrea Clematis. "TMAinspect, an EGEE Framework for Tissue MicroArray Image Handling". W 2008 8th IEEE International Symposium on Cluster Computing and the Grid (CCGrid). IEEE, 2008. http://dx.doi.org/10.1109/ccgrid.2008.100.
Pełny tekst źródła"SCORING OF BREAST TISSUE MICROARRAY SPOTS THROUGH ORDINAL REGRESSION". W International Conference on Computer Vision Theory and Applications. SciTePress - Science and and Technology Publications, 2009. http://dx.doi.org/10.5220/0001808202430248.
Pełny tekst źródłaZhou, A., Z. Zhou i P. Chen. "Microarray Analysis of Noncoding RNA in Lung Tissue of COPD Patients". W American Thoracic Society 2019 International Conference, May 17-22, 2019 - Dallas, TX. American Thoracic Society, 2019. http://dx.doi.org/10.1164/ajrccm-conference.2019.199.1_meetingabstracts.a5381.
Pełny tekst źródłaNguyen, Hoai-Nam, Charles Kervrann, Cyril Cauchois i Vincent Paveau. "Automatic core segmentation and registration for fast tissue microarray de-arraying". W 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI 2015). IEEE, 2015. http://dx.doi.org/10.1109/isbi.2015.7164147.
Pełny tekst źródłaAmaral, Telmo, Stephen McKenna, Katherine Robertson i Alastair Thompson. "Classification of breast-tissue microarray spots using colour and local invariants". W 2008 5th IEEE International Symposium on Biomedical Imaging (ISBI 2008). IEEE, 2008. http://dx.doi.org/10.1109/isbi.2008.4541167.
Pełny tekst źródłaRaporty organizacyjne na temat "Tissue microarray"
Dolled-Filhart, Marisa. Tissue Microarray Based Investigation of Stat3 Signaling Pathway in Breast Cancer. Fort Belvoir, VA: Defense Technical Information Center, maj 2004. http://dx.doi.org/10.21236/ada425703.
Pełny tekst źródłaMehra, Rohit. Tissue Microarray Assessment of Novel Prostate Cancer Biomarkers AMACR and EZH2 and Immunologic Response to Them in African-American and Caucasian Men. Fort Belvoir, VA: Defense Technical Information Center, kwiecień 2007. http://dx.doi.org/10.21236/ada470995.
Pełny tekst źródłaMeir, Shimon, Michael S. Reid, Cai-Zhong Jiang, Amnon Lers i Sonia Philosoph-Hadas. Molecular Studies of Postharvest Leaf and Flower Senescence. United States Department of Agriculture, styczeń 2011. http://dx.doi.org/10.32747/2011.7592657.bard.
Pełny tekst źródłaRimm, David L. Spectral Analysis of Breast Cancer on Tissue Microarrays: Seeing Beyond Morphology. Fort Belvoir, VA: Defense Technical Information Center, maj 2003. http://dx.doi.org/10.21236/ada417663.
Pełny tekst źródłaRimm, David L. Outcome Based Screening for Prognostic Phospho-RTK (Receptor Tyrosine Kinase) Antibodies Using Tissue Microarrays. Fort Belvoir, VA: Defense Technical Information Center, sierpień 2002. http://dx.doi.org/10.21236/ada410085.
Pełny tekst źródłaRimm, David. Outcome Based Screening for Prognostic Phospho-RTK (Receptor Tyrosine Kinase) Antibodies Using Tissue Microarrays). Fort Belvoir, VA: Defense Technical Information Center, sierpień 2004. http://dx.doi.org/10.21236/ada430123.
Pełny tekst źródłaRimm, David L. Outcome Based Screening for Prognostic Phospho-RTK (Receptor Tyrosine Kinase) Antibodies Using Tissue Microarrays. Fort Belvoir, VA: Defense Technical Information Center, sierpień 2003. http://dx.doi.org/10.21236/ada420064.
Pełny tekst źródłaGinzberg, Idit, i Walter De Jong. Molecular genetic and anatomical characterization of potato tuber skin appearance. United States Department of Agriculture, wrzesień 2008. http://dx.doi.org/10.32747/2008.7587733.bard.
Pełny tekst źródłaDroby, Samir, Michael Wisniewski, Ron Porat i Dumitru Macarisin. Role of Reactive Oxygen Species (ROS) in Tritrophic Interactions in Postharvest Biocontrol Systems. United States Department of Agriculture, grudzień 2012. http://dx.doi.org/10.32747/2012.7594390.bard.
Pełny tekst źródłaHeifetz, Yael, i Michael Bender. Success and failure in insect fertilization and reproduction - the role of the female accessory glands. United States Department of Agriculture, grudzień 2006. http://dx.doi.org/10.32747/2006.7695586.bard.
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