pmartR Software Overview The pmartR package provides a single software tool for QC (filtering and normalization), exploratory data analysis (EDA), and statistical analysis (robust to missing data) and includes numerous visualization capabilities of mass spectrometry (MS) omics data (proteomic...
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Last updated on 2024-02-11T22:41:43+00:00 by LN Anderson Omics-LHV Profiling of Host Response to MERS-CoV Virus Infection Background Middle East Respiratory Syndrome coronavirus ( MERS-CoV ), part of the Coronaviridae family, is classified as a Category C priority pathogen by the National Institute...
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Last updated on 2024-02-11T22:41:43+00:00 by LN Anderson Omics-LHV Profiling of Host Response to Ebola Virus Infection Background Ebola virus ( EBOV ) is a high risk biological agent, belonging to the Flaviviridae family, and is classified as a Category A priority pathogen by the National Institute...
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Last updated on 2024-02-11T22:41:43+00:00 by LN Anderson Omics-LHV Profiling of Host Response to Influenza A Virus Infection Background Influenza A virus ( IAV ) is a high risk biological agent belonging to the Orthomyxoviridae family is classified as a Category C priority pathogen by the National...
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Last updated on 2024-02-11T22:41:43+00:00 by LN Anderson Omics-LHV Profiling of Host Response to West Nile Virus Infection Background West Nile virus ( WNV ) belongs to the mosquito-borne Flaviviridae family and is classified as a Category A priority pathogen by the National Institute of Allergy and...
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Last updated on 2024-02-11T22:41:43+00:00 by LN Anderson Omics-LHV Profiling of Host Interferon-Stimulated Response to Virus Infection Background The human host Interferon ( IFN ) alpha, beta, and gamma participate in the body's natural immune response to lethal virus infection and disease. The...
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Machine learning is a core technology that is rapidly advancing within type 1 diabetes (T1D) research. Our Human Islet Research Network (HIRN) grant is studying early cellular response initiating β cell stress in T1D through the generation of heterogenous low- and high-throughput molecular...
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The Environmental Determinants of Diabetes in the Young (TEDDY) study is searching for factors influencing the development of type 1 diabetes (T1D) in children. Research has shown that there are certain genes that correlate to higher risk of developing T1D, but not all children with these genes...
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The Diabetes Autoimmunity Study in the Young (DAISY) seeks to find environmental factors that can trigger the development of type 1 diabetes (T1D) in children. DAISY follows children with high-risk of developing T1D based on family history or genetic markers. Genes, diets, infections, and...
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