Zobrazeno 1 - 10
of 61
pro vyhledávání: '"Massimo Andreatta"'
Autor:
Massimo Andreatta, Léonard Hérault, Paul Gueguen, David Gfeller, Ariel J. Berenstein, Santiago J. Carmona
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-13 (2024)
Abstract Batch effects in single-cell RNA-seq data pose a significant challenge for comparative analyses across samples, individuals, and conditions. Although batch effect correction methods are routinely applied, data integration often leads to over
Externí odkaz:
https://doaj.org/article/d35b657fcd2e4fe8aefe46b618827fe8
Publikováno v:
Bio-Protocol, Vol 13, Iss 16 (2023)
T cells are endowed with T-cell antigen receptors (TCR) that give them the capacity to recognize specific antigens and mount antigen-specific adaptive immune responses. Because TCR sequences are distinct in each naïve T cell, they serve as molecular
Externí odkaz:
https://doaj.org/article/be7ed61071c04a7c86f38293265b7e23
Autor:
Massimo Andreatta, Jesus Corria-Osorio, Sören Müller, Rafael Cubas, George Coukos, Santiago J. Carmona
Publikováno v:
Nature Communications, Vol 12, Iss 1, Pp 1-19 (2021)
One challenge of single cell RNA sequencing analysis is how to consistently identify cell subtypes and states across different datasets. Here the authors propose the use of a reference single-cell atlas as a stable system of coordinates to characteri
Externí odkaz:
https://doaj.org/article/9f2f292884da42c48b6390b29c262e36
Autor:
Massimo Andreatta, Ariel Tjitropranoto, Zachary Sherman, Michael C Kelly, Thomas Ciucci, Santiago J Carmona
Publikováno v:
eLife, Vol 11 (2022)
CD4+ T cells are critical orchestrators of immune responses against a large variety of pathogens, including viruses. While multiple CD4+ T cell subtypes and their key transcriptional regulators have been identified, there is a lack of consistent defi
Externí odkaz:
https://doaj.org/article/c7a11d1e0d734fb28896b157112d9324
Autor:
Massimo Andreatta, Santiago J. Carmona
Publikováno v:
Computational and Structural Biotechnology Journal, Vol 19, Iss , Pp 3796-3798 (2021)
UCell is an R package for evaluating gene signatures in single-cell datasets. UCell signature scores, based on the Mann-Whitney U statistic, are robust to dataset size and heterogeneity, and their calculation demands less computing time and memory th
Externí odkaz:
https://doaj.org/article/dca7c04997214beab95a8de92cf94997
Autor:
Carolina Barra, Bruno Alvarez, Sinu Paul, Alessandro Sette, Bjoern Peters, Massimo Andreatta, Søren Buus, Morten Nielsen
Publikováno v:
Genome Medicine, Vol 10, Iss 1, Pp 1-15 (2018)
Abstract Background Major histocompatibility complex class II (MHC-II) molecules present peptide fragments to T cells for immune recognition. Current predictors for peptide to MHC-II binding are trained on binding affinity data, generated in vitro an
Externí odkaz:
https://doaj.org/article/215cc6667adf4b839c3cd25b83214bef
Autor:
Sandeep Kumar Dhanda, Edita Karosiene, Lindy Edwards, Alba Grifoni, Sinu Paul, Massimo Andreatta, Daniela Weiskopf, John Sidney, Morten Nielsen, Bjoern Peters, Alessandro Sette
Publikováno v:
Frontiers in Immunology, Vol 9 (2018)
BackgroundPrediction of T cell immunogenicity is a topic of considerable interest, both in terms of basic understanding of the mechanisms of T cells responses and in terms of practical applications. HLA binding affinity is often used to predict T cel
Externí odkaz:
https://doaj.org/article/616418dcf51d4225980b56cc6b094182
Autor:
Francisco S Roque, Peter B Jensen, Henriette Schmock, Marlene Dalgaard, Massimo Andreatta, Thomas Hansen, Karen Søeby, Søren Bredkjær, Anders Juul, Thomas Werge, Lars J Jensen, Søren Brunak
Publikováno v:
PLoS Computational Biology, Vol 7, Iss 8, p e1002141 (2011)
Electronic patient records remain a rather unexplored, but potentially rich data source for discovering correlations between diseases. We describe a general approach for gathering phenotypic descriptions of patients from medical records in a systemat
Externí odkaz:
https://doaj.org/article/99ba46806dcc46edb876c08be452b359
Publikováno v:
PLoS ONE, Vol 6, Iss 11, p e26781 (2011)
Recent advances in high-throughput technologies have made it possible to generate both gene and protein sequence data at an unprecedented rate and scale thereby enabling entirely new "omics"-based approaches towards the analysis of complex biological
Externí odkaz:
https://doaj.org/article/8923caeaebfc477193fab5828006856f
Publikováno v:
PLoS ONE, Vol 5, Iss 10, p e13680 (2010)
BackgroundAlthough the majority of bacteria are innocuous or even beneficial for their host, others are highly infectious pathogens that can cause widespread and deadly diseases. When investigating the relationships between bacteria and other living
Externí odkaz:
https://doaj.org/article/a9a73ba9573a4e84a90b15063f1791b4