Zobrazeno 1 - 10
of 74
pro vyhledávání: '"Irene Papatheodorou"'
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-17 (2023)
Abstract The growing number of available single-cell gene expression datasets from different species creates opportunities to explore evolutionary relationships between cell types across species. Cross-species integration of single-cell RNA-sequencin
Externí odkaz:
https://doaj.org/article/0358fae52340410ea709b929061832b1
Autor:
Esra Katkat, Yeliz Demirci, Guillaume Heger, Doga Karagulle, Irene Papatheodorou, Alvis Brazma, Gunes Ozhan
Publikováno v:
Frontiers in Cell and Developmental Biology, Vol 11 (2023)
Melanoma is the deadliest form of skin cancer and develops from the melanocytes that are responsible for the pigmentation of the skin. The skin is also a highly regenerative organ, harboring a pool of undifferentiated melanocyte stem cells that proli
Externí odkaz:
https://doaj.org/article/5f92aee756d64bd5b2de22225f6c8555
Autor:
Albert Burger, Richard A. Baldock, David J. Adams, Shahida Din, Irene Papatheodorou, Michael Glinka, Bill Hill, Derek Houghton, Mehran Sharghi, Michael Wicks, Mark J. Arends
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 23, Iss 1, Pp 1-17 (2023)
Abstract Background The Human Cell Atlas resource will deliver single cell transcriptome data spatially organised in terms of gross anatomy, tissue location and with images of cellular histology. This will enable the application of bioinformatics ana
Externí odkaz:
https://doaj.org/article/5036c98cb2794b52894100234eea3c03
Autor:
Mathias Walzer, David García-Seisdedos, Ananth Prakash, Paul Brack, Peter Crowther, Robert L. Graham, Nancy George, Suhaib Mohammed, Pablo Moreno, Irene Papatheodorou, Simon J. Hubbard, Juan Antonio Vizcaíno
Publikováno v:
Scientific Data, Vol 9, Iss 1, Pp 1-15 (2022)
Abstract The number of mass spectrometry (MS)-based proteomics datasets in the public domain keeps increasing, particularly those generated by Data Independent Acquisition (DIA) approaches such as SWATH-MS. Unlike Data Dependent Acquisition datasets,
Externí odkaz:
https://doaj.org/article/a546f8015278497faae0aa68412d02c4
Autor:
Michael N. Wicks, Michael Glinka, Bill Hill, Derek Houghton, Mehran Sharghi, Ingrid Ferreira, David Adams, Shahida Din, Irene Papatheodorou, Kathryn Kirkwood, Michael Cheeseman, Albert Burger, Richard A. Baldock, Mark J. Arends
Publikováno v:
Journal of Pathology Informatics, Vol 14, Iss , Pp 100328- (2023)
Pathologists need to compare histopathological images of normal and diseased tissues between different samples, cases, and species. We have designed an interactive system, termed Comparative Pathology Workbench (CPW), which allows direct and dynamic
Externí odkaz:
https://doaj.org/article/234a0f909ea7415a89096b32fb3d9605
Autor:
Manik Garg, Xu Li, Pablo Moreno, Irene Papatheodorou, Yuelong Shu, Alvis Brazma, Zhichao Miao
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-10 (2021)
Abstract Several single-cell RNA sequencing (scRNA-seq) studies analyzing immune response to COVID-19 infection have been recently published. Most of these studies have small sample sizes, which limits the conclusions that can be made with high confi
Externí odkaz:
https://doaj.org/article/55a1b374726a4f5db7bba5e13a76da49
Autor:
Chengxin Dai, Anja Füllgrabe, Julianus Pfeuffer, Elizaveta M. Solovyeva, Jingwen Deng, Pablo Moreno, Selvakumar Kamatchinathan, Deepti Jaiswal Kundu, Nancy George, Silvie Fexova, Björn Grüning, Melanie Christine Föll, Johannes Griss, Marc Vaudel, Enrique Audain, Marie Locard-Paulet, Michael Turewicz, Martin Eisenacher, Julian Uszkoreit, Tim Van Den Bossche, Veit Schwämmle, Henry Webel, Stefan Schulze, David Bouyssié, Savita Jayaram, Vinay Kumar Duggineni, Patroklos Samaras, Mathias Wilhelm, Meena Choi, Mingxun Wang, Oliver Kohlbacher, Alvis Brazma, Irene Papatheodorou, Nuno Bandeira, Eric W. Deutsch, Juan Antonio Vizcaíno, Mingze Bai, Timo Sachsenberg, Lev I. Levitsky, Yasset Perez-Riverol
Publikováno v:
Nature Communications, Vol 12, Iss 1, Pp 1-8 (2021)
The number of publicly available proteomics datasets is growing rapidly, but a standardized approach for describing the associated metadata is lacking. Here, the authors propose a format and a software pipeline to present and validate metadata, and i
Externí odkaz:
https://doaj.org/article/33519ff7742042fb963af4bf5ef059fa
Autor:
Shengbo Wang, David García-Seisdedos, Ananth Prakash, Deepti Jaiswal Kundu, Andrew Collins, Nancy George, Silvie Fexova, Pablo Moreno, Irene Papatheodorou, Andrew R Jones, Juan Antonio Vizcaíno
Publikováno v:
PLoS Computational Biology, Vol 18, Iss 6, p e1010174 (2022)
The increasingly large amount of proteomics data in the public domain enables, among other applications, the combined analyses of datasets to create comparative protein expression maps covering different organisms and different biological conditions.
Externí odkaz:
https://doaj.org/article/849f32e493854c30839c111727f66dc3
Autor:
Andrew F. Jarnuczak, Hanna Najgebauer, Mitra Barzine, Deepti J. Kundu, Fatemeh Ghavidel, Yasset Perez-Riverol, Irene Papatheodorou, Alvis Brazma, Juan Antonio Vizcaíno
Publikováno v:
Scientific Data, Vol 8, Iss 1, Pp 1-14 (2021)
Abstract Using 11 proteomics datasets, mostly available through the PRIDE database, we assembled a reference expression map for 191 cancer cell lines and 246 clinical tumour samples, across 13 lineages. We found unique peptides identified only in tum
Externí odkaz:
https://doaj.org/article/b91373af618f49f2b3ea1c128209c620
Autor:
Yanhui Hu, Sudhir Gopal Tattikota, Yifang Liu, Aram Comjean, Yue Gao, Corey Forman, Grace Kim, Jonathan Rodiger, Irene Papatheodorou, Gilberto dos Santos, Stephanie E. Mohr, Norbert Perrimon
Publikováno v:
Computational and Structural Biotechnology Journal, Vol 19, Iss , Pp 2018-2026 (2021)
With the advent of single-cell RNA sequencing (scRNA-seq) technologies, there has been a spike in studies involving scRNA-seq of several tissues across diverse species including Drosophila. Although a few databases exist for users to query genes of i
Externí odkaz:
https://doaj.org/article/cf38f4fae56a418babd5d8cc72ee12c5