Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Debmalya Nandy"'
Autor:
Benjamin S. Frank, Debmalya Nandy, Ludmila Khailova, Max B. Mitchell, Gareth J. Morgan, Mark Twite, Michael V. DiMaria, Jesse A. Davidson
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-11 (2023)
Abstract Children with single ventricle heart disease (SVHD) experience morbidity due to inadequate pulmonary blood flow. Using proteomic screening, our group previously identified members of the matrix metalloproteinase (MMP), tissue inhibitor of me
Externí odkaz:
https://doaj.org/article/b36dc46c478f44bd8d5c93238571632d
Publikováno v:
BMC Bioinformatics, Vol 23, Iss 1, Pp 1-17 (2022)
Abstract When analyzing large datasets from high-throughput technologies, researchers often encounter missing quantitative measurements, which are particularly frequent in metabolomics datasets. Metabolomics, the comprehensive profiling of metabolite
Externí odkaz:
https://doaj.org/article/ce408c908a7843cfaa11e6d594a04f11
Autor:
Iain R. Konigsberg, Bret Barnes, Monica Campbell, Elizabeth Davidson, Yingfei Zhen, Olivia Pallisard, Meher Preethi Boorgula, Corey Cox, Debmalya Nandy, Souvik Seal, Kristy Crooks, Evan Sticca, Genelle F. Harrison, Andrew Hopkinson, Alexis Vest, Cosby G. Arnold, Michael G. Kahn, David P. Kao, Brett R. Peterson, Stephen J. Wicks, Debashis Ghosh, Steve Horvath, Wanding Zhou, Rasika A. Mathias, Paul J. Norman, Rishi Porecha, Ivana V. Yang, Christopher R. Gignoux, Andrew A. Monte, Alem Taye, Kathleen C. Barnes
Publikováno v:
Communications Medicine, Vol 1, Iss 1, Pp 1-10 (2021)
Konigsberg et al. profile DNA methylation in blood samples from SARS-CoV-2 cases and controls. The authors use machine learning to classify infected vs. non-infected individuals and predict clinical outcomes related to disease severity.
Externí odkaz:
https://doaj.org/article/4065c7ad16474661ad9788df11b18ed6
Publikováno v:
F1000Research. 11:759
Background: Magnetic resonance imaging (MRI) in clinical patients is often evaluated for diagnostic purposes. However, to develop a disease classifier, imaging data can be “noisy”, as in being heterogeneous (e.g., obtained from multiple sites), h
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::eac4d43edfc6737bb2a7241e9e6d6546
https://doi.org/10.12688/f1000research.117334.1
https://doi.org/10.12688/f1000research.117334.1
Autor:
Bret Barnes, David P. Kao, Alem Taye, Andrew Hopkinson, Evan Sticca, Brett R. Peterson, Wanding Zhou, Elizabeth J. Davidson, Genelle F. Harrison, Rishi Porecha, Michael G. Kahn, Debmalya Nandy, Corey Cox, Kristy Crooks, Alexis Vest, Cosby G. Arnold, Steve Horvath, Ivana V. Yang, Andrew A. Monte, Yingfei Zhen, Kathleen C. Barnes, Paul Norman, Debashis Ghosh, Rasika A. Mathias, Monica Campbell, Christopher R. Gignoux, Souvik Seal, Iain R. Konigsberg, Olivia Pallisard, Stephen J. Wicks, Meher Preethi Boorgula
Since the onset of the SARS-CoV-2 pandemic, most clinical testing has focused on RT-PCR1. Host epigenome manipulation post coronavirus infection2–4 suggests that DNA methylation signatures may differentiate patients with SARS-CoV-2 infection from u
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::17e12fe5f3f6e7102b0873edb8c1d695
https://doi.org/10.21203/rs.3.rs-334297/v1
https://doi.org/10.21203/rs.3.rs-334297/v1
Publikováno v:
J Am Stat Assoc
Contemporary high-throughput experimental and surveying techniques give rise to ultrahigh-dimensional supervised problems with sparse signals; that is, a limited number of observations (n), each with a very large number of covariates (p≫n), only a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bf6569d3ea117c4fe699b76137aef5d1
Building upon recent research on the applications of the density information matrix, we develop a tool for sufficient dimension reduction (SDR) in regression problems called covariate information m...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2c5a0f77a98de423ceae4da22de86ae3
http://hdl.handle.net/11382/527353
http://hdl.handle.net/11382/527353