Zobrazeno 1 - 10
of 42
pro vyhledávání: '"Luke, Zappia"'
Publikováno v:
Genome Biology, Vol 22, Iss 1, Pp 1-16 (2021)
Abstract Population-scale single-cell RNA sequencing (scRNA-seq) is now viable, enabling finer resolution functional genomics studies and leading to a rush to adapt bulk methods and develop new single-cell-specific methods to perform these studies. S
Externí odkaz:
https://doaj.org/article/f967b00b2e7e43a18172628e469a5e6f
Autor:
Luke Zappia, Fabian J. Theis
Publikováno v:
Genome Biology, Vol 22, Iss 1, Pp 1-18 (2021)
Abstract Recent years have seen a revolution in single-cell RNA-sequencing (scRNA-seq) technologies, datasets, and analysis methods. Since 2016, the scRNA-tools database has cataloged software tools for analyzing scRNA-seq data. With the number of to
Externí odkaz:
https://doaj.org/article/f5ca1e7ff8744bfbb069bcd39ac4e09a
Autor:
David S. Fischer, Leander Dony, Martin König, Abdul Moeed, Luke Zappia, Lukas Heumos, Sophie Tritschler, Olle Holmberg, Hananeh Aliee, Fabian J. Theis
Publikováno v:
Genome Biology, Vol 22, Iss 1, Pp 1-21 (2021)
Abstract Single-cell RNA-seq datasets are often first analyzed independently without harnessing model fits from previous studies, and are then contextualized with public data sets, requiring time-consuming data wrangling. We address these issues with
Externí odkaz:
https://doaj.org/article/42d3581d43904bdf861e73681f736824
Publikováno v:
Genome Biology, Vol 21, Iss 1, Pp 1-16 (2020)
Abstract Long-read technologies are overcoming early limitations in accuracy and throughput, broadening their application domains in genomics. Dedicated analysis tools that take into account the characteristics of long-read data are thus required, bu
Externí odkaz:
https://doaj.org/article/79ac667da73342cfbc0213536936419d
Autor:
Michael G. Leeming, Andrew P. Isaac, Luke Zappia, Richard A.J. O’Hair, William A. Donald, Bernard J. Pope
Publikováno v:
SoftwareX, Vol 12, Iss , Pp 100559- (2020)
The identification of metabolites plays an important role in understanding drug efficacy and safety however these compounds are often difficult to identify in complex mixtures. One approach to identify drug metabolites involves utilising differential
Externí odkaz:
https://doaj.org/article/9d262ac641b94230a8142455002a4fc9
Publikováno v:
Genome Medicine, Vol 11, Iss 1, Pp 1-15 (2019)
Abstract Background Human kidney organoids hold promise for studying development, disease modelling and drug screening. However, the utility of stem cell-derived kidney tissues will depend on how faithfully these replicate normal fetal development at
Externí odkaz:
https://doaj.org/article/6ade7031b0f441068b1deadddbdacf8f
Publikováno v:
Genome Biology, Vol 18, Iss 1, Pp 1-15 (2017)
Abstract As single-cell RNA sequencing (scRNA-seq) technologies have rapidly developed, so have analysis methods. Many methods have been tested, developed, and validated using simulated datasets. Unfortunately, current simulations are often poorly do
Externí odkaz:
https://doaj.org/article/5d422a36cad040bead5549d96c85a0e2
Autor:
Kynan T Lawlor, Luke Zappia, James Lefevre, Joo-Seop Park, Nicholas A Hamilton, Alicia Oshlack, Melissa H Little, Alexander N Combes
Publikováno v:
eLife, Vol 8 (2019)
Progenitor self-renewal and differentiation is often regulated by spatially restricted cues within a tissue microenvironment. Here, we examine how progenitor cell migration impacts regionally induced commitment within the nephrogenic niche in mice. W
Externí odkaz:
https://doaj.org/article/346dcaa82adf4a93883b05f34c9ad703
Publikováno v:
PLoS Computational Biology, Vol 14, Iss 6, p e1006245 (2018)
As single-cell RNA-sequencing (scRNA-seq) datasets have become more widespread the number of tools designed to analyse these data has dramatically increased. Navigating the vast sea of tools now available is becoming increasingly challenging for rese
Externí odkaz:
https://doaj.org/article/3140af411481403cafe5e23596ab7fc9
Autor:
Karin Hrovatin, Aimée Bastidas-Ponce, Mostafa Bakhti, Luke Zappia, Maren Büttner, Ciro Sallino, Michael Sterr, Anika Böttcher, Adriana Migliorini, Heiko Lickert, Fabian J. Theis
Multiple pancreatic islet single-cell RNA sequencing (scRNA-seq) datasets have been generated to study development, homeostasis, and diabetes. However, there is no consensus on cell states and pathways across conditions as well as the value of precli
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c06fe0cc7eaed6a29f83358420bb9216
https://doi.org/10.1101/2022.12.22.521557
https://doi.org/10.1101/2022.12.22.521557
