Zobrazeno 1 - 10
of 29
pro vyhledávání: '"Qihuang Zhang"'
Leveraging spatial transcriptomics data to recover cell locations in single-cell RNA-seq with CeLEry
Autor:
Qihuang Zhang, Shunzhou Jiang, Amelia Schroeder, Jian Hu, Kejie Li, Baohong Zhang, David Dai, Edward B. Lee, Rui Xiao, Mingyao Li
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-19 (2023)
Abstract Single-cell RNA sequencing (scRNA-seq) has revolutionized our understanding of cellular heterogeneity in health and disease. However, the lack of physical relationships among dissociated cells has limited its applications. To address this is
Externí odkaz:
https://doaj.org/article/211cff1dc45b4b52ab015e67533383d8
Autor:
Giselle C Matlis, Qihuang Zhang, Emilie J Benson, M Katie Weeks, Kristen Andersen, Jharna Jahnavi, Alec Lafontant, Jake Breimann, Thomas Hallowell, Yuxi Lin, Daniel J Licht, Arjun G Yodh, Todd J Kilbaugh, Rodrigo M Forti, Brian R White, Wesley B Baker, Rui Xiao, Tiffany S Ko
Publikováno v:
PLoS ONE, Vol 19, Iss 7, p e0305254 (2024)
Advanced optical neuromonitoring of cerebral hemodynamics with hybrid diffuse optical spectroscopy (DOS) and diffuse correlation spectroscopy (DCS) methods holds promise for non-invasive characterization of brain health in critically ill patients. Ho
Externí odkaz:
https://doaj.org/article/7eb3bbb0e763410fb1775119e59a3caa
Autor:
Anindya Sen, Nathaniel T. Stevens, N. Ken Tran, Rishav R. Agarwal, Qihuang Zhang, Joel A. Dubin
Publikováno v:
Frontiers in Public Health, Vol 11 (2023)
IntroductionThere is a vast literature on the performance of different short-term forecasting models for country specific COVID-19 cases, but much less research with respect to city level cases. This paper employs daily case counts for 25 Metropolita
Externí odkaz:
https://doaj.org/article/c9061bb31e0a4dd6a5b85ec3c3ca5847
Publikováno v:
PLoS ONE, Vol 18, Iss 2, p e0277878 (2023)
While the impact of the COVID-19 pandemic has been widely studied, relatively fewer discussions about the sentimental reaction of the public are available. In this article, we scrape COVID-19 related tweets on the microblogging platform, Twitter, and
Externí odkaz:
https://doaj.org/article/023d23a22d0142bfa3d43ddd963b7c3f
Publikováno v:
PLoS ONE, Vol 16, Iss 1, p e0244536 (2021)
BackgroundSince March 11, 2020 when the World Health Organization (WHO) declared the COVID-19 pandemic, the number of infected cases, the number of deaths, and the number of affected countries have climbed rapidly. To understand the impact of COVID-1
Externí odkaz:
https://doaj.org/article/73afd5f43060481c926fba7335eea9e1
Publikováno v:
Economic Analysis and Policy. 78:225-242
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::919013dc43ca2cefaa80591f18849da9
https://doi.org/10.1016/j.eap.2023.03.006
https://doi.org/10.1016/j.eap.2023.03.006
Autor:
Stefan H. Steiner, Anindya Sen, Nathaniel T. Stevens, Francis Kiwon, Qihuang Zhang, Plinio P. Morita
Publikováno v:
Canadian Public Policy. 48:144-161
This study uses coronavirus disease 2019 (COVID-19) case counts and Google mobility data for 12 of Ontario's largest Public Health Units from Spring 2020 until the end of January 2021 to evaluate the effects of non-pharmaceutical interventions (NPIs;
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2989c414ca1f4ffbed04f147a6a84329
https://doi.org/10.3138/cpp.2021-022
https://doi.org/10.3138/cpp.2021-022
Publikováno v:
Briefings in Bioinformatics. 23
Cell-type composition of intact bulk tissues can vary across samples. Deciphering cell-type composition and its changes during disease progression is an important step toward understanding disease pathogenesis. To infer cell-type composition, existin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::80125549282e01de97a306da4ad5938b
https://doi.org/10.1093/bib/bbac430
https://doi.org/10.1093/bib/bbac430
Autor:
Grace Yi, Qihuang Zhang
Publikováno v:
BiometricsREFERENCES.
Zero-inflated count data arise frequently from genomics studies. Analysis of such data is often based on a mixture model which facilitates excess zeros in combination with a Poisson distribution, and various inference methods have been proposed under
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d687476117635a520e4885132286c774
https://pubmed.ncbi.nlm.nih.gov/35261029
https://pubmed.ncbi.nlm.nih.gov/35261029
Autor:
Grace Yi, Qihuang Zhang
Publikováno v:
J Appl Stat
Autoregressive (AR) models are useful tools in time series analysis. Inferences under such models are distorted in the presence of measurement error, which is very common in practice. In this article, we establish analytical results for quantifying t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fe7fd33dee8b40654ec73105bbdb4d93
