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DTSTART;TZID=America/Chicago:20240522T110000
DTEND;TZID=America/Chicago:20240522T133000
DTSTAMP:20260522T021121
CREATED:20220330T204527Z
LAST-MODIFIED:20240305T214957Z
UID:672413-1716375600-1716384600@dev-site.sph.umn.edu
SUMMARY:Faculty and Staff Recognition Celebration
DESCRIPTION:Redirect to: https://www.sph.umn.edu/events-calendar/faculty-staff-recognition/
URL:https://dev-site.sph.umn.edu/event/faculty-and-staff-recognition-celebration/
LOCATION:McNamara Alumni Center\, 200 SE Oak St\, Minneapolis\, MN\, 55414\, United States
CATEGORIES:Faculty/Staff
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BEGIN:VEVENT
DTSTART;TZID=America/Chicago:20240522T120000
DTEND;TZID=America/Chicago:20240522T130000
DTSTAMP:20260522T021121
CREATED:20240508T205928Z
LAST-MODIFIED:20240508T205928Z
UID:687690-1716379200-1716382800@dev-site.sph.umn.edu
SUMMARY:Mobilization of an ambulatory veterinary clinic to Ukraine: Notes from the field
DESCRIPTION:Join us for a conversation with Jon Geller about pets and the war in Ukraine on Wednesday May 22nd. Food will be provided from 12:00 p.m. – 1:00 p.m.
URL:https://dev-site.sph.umn.edu/event/mobilization-of-an-ambulatory-veterinary-clinic-to-ukraine-notes-from-the-field/
LOCATION:Blegen Hall
CATEGORIES:Current Students,Faculty/Staff
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DTSTART;TZID=America/Chicago:20240523T150000
DTEND;TZID=America/Chicago:20240523T163000
DTSTAMP:20260522T021121
CREATED:20240221T151032Z
LAST-MODIFIED:20240221T151032Z
UID:686166-1716476400-1716481800@dev-site.sph.umn.edu
SUMMARY:2024 Robert L. Kane Memorial Lecture
DESCRIPTION:[vc_row][vc_column][vc_column_text] \nGreen House Nursing Homes: More Than a Promising Innovation \nThis presentation\, by Dr. Sheryl Zimmerman\, Ms. Susan Ryan (CEO of the Center for Innovation\, the parent organization of the Green House Project and Pioneer Network)\, and Ms. Melissa Schneider (COO of Episcopal Homes\, a local Minnesota Green House home)\, will describe Green House homes; research related to care and outcomes; and the future of Green House homes in the U.S. and abroad. \n[/vc_column_text][/vc_column][/vc_row]
URL:https://dev-site.sph.umn.edu/event/2024-robert-l-kane-memorial-lecture/
LOCATION:hybrid: Campus Club or zoom\, 300 Washington Avenue Southeast Coffman Memorial Union\, 4th Floor\, Minneapolis\, MN\, 55455\, United States
CATEGORIES:Alumni,Current Students,Faculty/Staff,General Public
ATTACH;FMTTYPE=image/jpeg:https://dev-site.sph.umn.edu/wp-content/uploads/2024/02/coffman.jpg
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DTSTART;TZID=America/Chicago:20240529T100000
DTEND;TZID=America/Chicago:20240529T110000
DTSTAMP:20260522T021121
CREATED:20240528T170943Z
LAST-MODIFIED:20240528T170943Z
UID:687861-1716976800-1716980400@dev-site.sph.umn.edu
SUMMARY:BHDS Plan B Presentation with Cheng-Chang Wu
DESCRIPTION:Comparative Evaluation of Missing Data Imputation for Omics Data \nPresented by Cheng-Chang Wu\nMasters Candidate in Biostatistics \nPlan B Adviser: Eric Lock \nAbstract: Missing data is a common challenge for the analysis of many molecular “omics” datasets (e.g.\, genomics\, metabolomics\, proteomics). This challenge is particularly significant in metabolomics and other mass-spectrometry based technologies\, primarily due to the prevalence of informative missingness\, such as data Missing Due to Limit of Detection (MLOD). This study evaluated two widely-used imputation methods\, SoftImpute and KNNimpute\, across a variety of parameter settings\, for estimating missing values in simulated datasets under diverse conditions. These conditions included varying data dimensions\, signal-to-noise ratios\, missing data proportions\, and missingness mechanisms (Missing Completely at Random and MLOD). Additionally\, the methods were applied to a real metabolomics dataset from the MILK-OMICS study. \nWe show that the SVD-based SoftImpute consistently outperforms the neighborhood-based KNNimpute across all simulations\, likely due to its ability to capture the low-rank structure inherent in the simulated data. SoftImpute’s performance is further influenced by the adopted tuning approaches and parameter settings. Notably\, the nuclear norm regularization proves effective in providing stable solutions and mitigating over-fitting issues\, especially under scenarios with weak signal strength. While fine-tuning the rank of the approximation for imputations may yield superior results\, it also exhibits instability without nuclear norm penalization. These findings underscore the importance of parameter settings and tuning approaches for SoftImpute to ensure optimal imputation accuracy. Although simulations highlight SoftImpute’s advantages\, the application to real metabolomics data reveals limitations of current methods in handling missingness induced by detection limit. Nonetheless\, these insights can guide the development of more effective imputation strategies suited to the challenges of omics data analysis. \nKeywords: Missing data imputation\, Omics data\, Metabolomics\, SoftImpute\, KNNimpute\, Simulations\, Low-rank approximation\, Missing due to limit of detection\, Nuclear norm regularization
URL:https://dev-site.sph.umn.edu/event/bhds-plan-b-presentation-with-cheng-chang-wu/
LOCATION:hybrid: in person at University Office Plaza\, Room 240 or zoom\, 2221 University Ave SE\, Minneapolis\, 55415\, United States
CATEGORIES:Current Students,Faculty/Staff
ATTACH;FMTTYPE=image/png:https://dev-site.sph.umn.edu/wp-content/uploads/2024/02/biostats-webpage-graphic-@3x.png
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