Zobrazeno 1 - 10
of 25
pro vyhledávání: '"Rafael Irizarry"'
Autor:
Phillip B. Nicol, Danielle Paulson, Gege Qian, X. Shirley Liu, Rafael Irizarry, Avinash D. Sahu
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-14 (2024)
Abstract Single-cell transcriptomics has emerged as a powerful tool for understanding how different cells contribute to disease progression by identifying cell types that change across diseases or conditions. However, detecting changing cell types is
Externí odkaz:
https://doaj.org/article/4f488a03a7a34c2f888328d58652862e
Autor:
Julian Hecker, Sanghun Lee, Priyadarshini Kachroo, Dmitry Prokopenko, Anna Maaser-Hecker, Sharon M. Lutz, Georg Hahn, Rafael Irizarry, Scott T. Weiss, Dawn L. DeMeo, Christoph Lange
Publikováno v:
Epigenetics, Vol 18, Iss 1 (2023)
ABSTRACTBackground: Recent studies have identified thousands of associations between DNA methylation CpGs and complex diseases/traits, emphasizing the critical role of epigenetics in understanding disease aetiology and identifying biomarkers. However
Externí odkaz:
https://doaj.org/article/ca2e6b037851433db0d38b74bde03ccd
Autor:
Mercedeh Movassagh, Sarah U. Morton, Christine Hehnly, Jasmine Smith, Trang T. Doan, Rafael Irizarry, James R. Broach, Steven J. Schiff, Jeffrey A. Bailey, Joseph N. Paulson
Publikováno v:
BMC Genomics, Vol 23, Iss 1, Pp 1-17 (2022)
Abstract We introduce mirTarRnaSeq, an R/Bioconductor package for quantitative assessment of miRNA-mRNA relationships within sample cohorts. mirTarRnaSeq is a statistical package to explore predicted or pre-hypothesized miRNA-mRNA relationships follo
Externí odkaz:
https://doaj.org/article/4ba6b9cc99ba479eb7c74c737024ba74
Autor:
Guo-Cheng Yuan, Long Cai, Michael Elowitz, Tariq Enver, Guoping Fan, Guoji Guo, Rafael Irizarry, Peter Kharchenko, Junhyong Kim, Stuart Orkin, John Quackenbush, Assieh Saadatpour, Timm Schroeder, Ramesh Shivdasani, Itay Tirosh
Publikováno v:
Genome Biology, Vol 18, Iss 1, Pp 1-8 (2017)
Abstract Single-cell analysis is a rapidly evolving approach to characterize genome-scale molecular information at the individual cell level. Development of single-cell technologies and computational methods has enabled systematic investigation of ce
Externí odkaz:
https://doaj.org/article/52a3f62434394e26b80ed3c3002e85e6
Autor:
Phillip B. Nicol, Danielle Paulson, Gege Qian, X. Shirley Liu, Rafael Irizarry, Avinash D. Sahu
Single-cell transcriptomics has emerged as a powerful tool for understanding how different cells contribute to disease progression by identifying cell types that change across diseases or conditions. However, detecting changing cell types is challeng
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a9c07a3c2fecf92e30896c607e8fa796
https://doi.org/10.1101/2023.05.06.539326
https://doi.org/10.1101/2023.05.06.539326
Autor:
Bärbel Schröfelbauer, Patrick K. Kimes, Paige Hauke, Charlotte E. Reid, Kevin Shao, Sarah J. Hill, Rafael Irizarry, William C. Hahn
Publikováno v:
Proceedings of the National Academy of Sciences. 120
Although antibodies targeting specific tumor-expressed antigens are the standard of care for some cancers, the identification of cancer-specific targets amenable to antibody binding has remained a bottleneck in development of new therapeutics. To ove
Unsupervised clustering of single-cell RNA-sequencing data enables the identification and discovery of distinct cell populations. However, the most widely used clustering algorithms are heuristic and do not formally account for statistical uncertaint
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::79f82e1e0f7f6e4754d8eb0c4075d782
https://doi.org/10.1101/2022.08.01.502383
https://doi.org/10.1101/2022.08.01.502383
Autor:
Mercedeh Movassagh, Sarah U. Morton, Christine Hehnly, Jasmine Smith, Trang T. Doan, Rafael Irizarry, James R. Broach, Steven J. Schiff, Jeffrey A. Bailey, Joseph N. Paulson
Publikováno v:
BMC genomics. 23(1)
We introduce mirTarRnaSeq, an R/Bioconductor package for quantitative assessment of miRNA-mRNA relationships within sample cohorts. mirTarRnaSeq is a statistical package to explore predicted or pre-hypothesized miRNA-mRNA relationships following targ
Publikováno v:
The Journal of Immunology. 208:172.18-172.18
Spatial transcriptomics enables spatially resolved gene expression measurements at near single-cell resolution. The detection of genes that are differentially expressed across tissue context for cell types of interest is an essential challenge for di
Autor:
Alexandra Schnell, Linglin Huang, Meromit Singer, Anvita Singaraju, Alina Bollhagen, Pratiksha I Thakore, Danielle Dionne, Toni M Delorey, Mathias Pawlak, Rafael Irizarry, Aviv Regev, Vijay K Kuchroo
Publikováno v:
The Journal of Immunology. 206:61.11-61.11
At homeostasis, most Th17 cells are found in the lamina propria of the intestine, where they contribute to tissue homeostasis by inhibiting microbiota from tissue invasion and promote barrier functions. Recent studies in humans and mice have implicat