Literatura científica selecionada sobre o tema "Immune repertoire visualization"
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Artigos de revistas sobre o assunto "Immune repertoire visualization"
Toby, Inimary, Scott Christley, Walter Scarborough, William H. Rounds, John Fonner, Stephen Mock, Nancy Monson, Richard H. Scheuermann e Lindsay G. Cowell. "VDJServer – a web-accessible analysis portal for immune repertoire sequencing analysis". Journal of Immunology 198, n.º 1_Supplement (1 de maio de 2017): 55.49. http://dx.doi.org/10.4049/jimmunol.198.supp.55.49.
Texto completo da fonteChen, Si-Yi, Tao Yue, Qian Lei e An-Yuan Guo. "TCRdb: a comprehensive database for T-cell receptor sequences with powerful search function". Nucleic Acids Research 49, n.º D1 (29 de setembro de 2020): D468—D474. http://dx.doi.org/10.1093/nar/gkaa796.
Texto completo da fonteSarda, Shrutii, Geoffrey Lowman, Michelle Toro, Loni Pickle, Timothy Looney e Fiona Hyland. "Fully Automated Workflows Quantify and Report Key T-Cell and B-Cell Receptor Biomarkers Relevant to Immuno-Oncology and Heme-Oncology Research". Blood 138, Supplement 1 (5 de novembro de 2021): 4002. http://dx.doi.org/10.1182/blood-2021-151154.
Texto completo da fonteOmer, Aviv, Or Shemesh, Ayelet Peres, Pazit Polak, Adrian J. Shepherd, Corey T. Watson, Scott D. Boyd, Andrew M. Collins, William Lees e Gur Yaari. "VDJbase: an adaptive immune receptor genotype and haplotype database". Nucleic Acids Research 48, n.º D1 (11 de outubro de 2019): D1051—D1056. http://dx.doi.org/10.1093/nar/gkz872.
Texto completo da fonteSauteraud, Renan, Lev Dashevskiy, Greg Finak e Raphael Gottardo. "ImmuneSpace: Enabling integrative modeling of human immunological data". Journal of Immunology 196, n.º 1_Supplement (1 de maio de 2016): 124.65. http://dx.doi.org/10.4049/jimmunol.196.supp.124.65.
Texto completo da fonteStalika, Evangelia, Anastasia Hadzidimitriou, Athanasios Gkoufas, Maria Karypidou, Semeli Mastrodemou, Anna Vardi, Vasilis Bikos et al. "High-Throughput Profiling of the T-Cell Receptor Gene Repertoire Supports Antigen Drive in the Pathogenesis of Chronic Idiopathic Neutropenia". Blood 124, n.º 21 (6 de dezembro de 2014): 2731. http://dx.doi.org/10.1182/blood.v124.21.2731.2731.
Texto completo da fonteGemenetzi, Katerina, Evangelia Stalika, Andreas Agathangelidis, Fotis Psomopoulos, Elisavet Vlachonikola, Chrysi Galigalidou, Symeon Metallidis et al. "Evidence for Epitope-Specific T Cell Responses in HIV-Associated Non Neoplastic Lymphadenopathy: High-Throughput Immunogenetic Evidence". Blood 132, Supplement 1 (29 de novembro de 2018): 1117. http://dx.doi.org/10.1182/blood-2018-99-118975.
Texto completo da fonteHuang, Alex Yee-Chen, Jay T. Myers, Youmna Othman, Deborah Sim Barkauskas e Agne Petrosiute. "Real-time dynamic and sequential tracking of tumor propagation and associated immune responses in the CNS microenvironment." Journal of Clinical Oncology 30, n.º 15_suppl (20 de maio de 2012): 9520. http://dx.doi.org/10.1200/jco.2012.30.15_suppl.9520.
Texto completo da fonteVetter, Julia, Constantin Aschauer, Andreas Heinzel, Roman Reindl-Schweighofer, Kira Jelencsics, Karin Hu, Rainer Oberbauer, Stephan Winkler e Susanne Schaller. "Identification of immunologic factors associated with allograft rejection using NGS T cell receptor repertoire data". Journal of Immunology 204, n.º 1_Supplement (1 de maio de 2020): 161.3. http://dx.doi.org/10.4049/jimmunol.204.supp.161.3.
Texto completo da fonteSturm, Gregor, Tamas Szabo, Georgios Fotakis, Marlene Haider, Dietmar Rieder, Zlatko Trajanoski e Francesca Finotello. "Scirpy: a Scanpy extension for analyzing single-cell T-cell receptor-sequencing data". Bioinformatics 36, n.º 18 (2 de julho de 2020): 4817–18. http://dx.doi.org/10.1093/bioinformatics/btaa611.
Texto completo da fonteTeses / dissertações sobre o assunto "Immune repertoire visualization"
Abdollahi, Nika. "B cell receptor repertoire analysis in clinical context : new approaches for clonal grouping, intra-clonal diversity studies, and repertoire visualization". Electronic Thesis or Diss., Sorbonne université, 2021. http://www.theses.fr/2021SORUS063.
Texto completo da fonteNext-generation sequencing has enabled researchers to conduct in-depth analyses of the immunological repertoire landscape. However, a significant concern in these studies is the computational cost of analyzing millions of sequences with inherent complexity, variability, and mutational capacity, imposing computational challenges and necessitating the development of efficient methods. This challenge is even more evident in the clinical context that does not necessarily have access to professionals with computing skills or robust computational resources. Thus, the main goal of this thesis is to develop a set of dedicated and integrated tools to be used in the clinical environment, for medical diagnostic and patient care, and in the research environment, to perform large-scale and in-depth repertoire analysis. We have designed and implemented multiple algorithms and gathered them in a user-friendly interactive BCR repertoire visualization pipeline to facilitate the process of integrating BCR repertoire analysis into medical practices