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1.
Nat Commun ; 13(1): 4678, 2022 08 09.
Article in English | MEDLINE | ID: covidwho-1984385

ABSTRACT

There are only a few platforms that integrate multiple omics data types, bioinformatics tools, and interfaces for integrative analyses and visualization that do not require programming skills. Here we present iLINCS ( http://ilincs.org ), an integrative web-based platform for analysis of omics data and signatures of cellular perturbations. The platform facilitates mining and re-analysis of the large collection of omics datasets (>34,000), pre-computed signatures (>200,000), and their connections, as well as the analysis of user-submitted omics signatures of diseases and cellular perturbations. iLINCS analysis workflows integrate vast omics data resources and a range of analytics and interactive visualization tools into a comprehensive platform for analysis of omics signatures. iLINCS user-friendly interfaces enable execution of sophisticated analyses of omics signatures, mechanism of action analysis, and signature-driven drug repositioning. We illustrate the utility of iLINCS with three use cases involving analysis of cancer proteogenomic signatures, COVID 19 transcriptomic signatures and mTOR signaling.


Subject(s)
COVID-19 , Neoplasms , COVID-19/genetics , Computational Biology , Humans , Neoplasms/genetics , Software , Transcriptome , Workflow
2.
J Am Med Inform Assoc ; 27(7): 1121-1125, 2020 07 01.
Article in English | MEDLINE | ID: covidwho-1066354

ABSTRACT

OBJECTIVE: The study sought to create an online resource that informs the public of coronavirus disease 2019 (COVID-19) outbreaks in their area. MATERIALS AND METHODS: This R Shiny application aggregates data from multiple resources that track COVID-19 and visualizes them through an interactive, online dashboard. RESULTS: The Web resource, called the COVID-19 Watcher, can be accessed online (https://covid19watcher.research.cchmc.org/). It displays COVID-19 data from every county and 188 metropolitan areas in the United States. Features include rankings of the worst-affected areas and auto-generating plots that depict temporal changes in testing capacity, cases, and deaths. DISCUSSION: The Centers for Disease Control and Prevention does not publish COVID-19 data for local municipalities, so it is critical that academic resources fill this void so the public can stay informed. The data used have limitations and likely underestimate the scale of the outbreak. CONCLUSIONS: The COVID-19 Watcher can provide the public with real-time updates of outbreaks in their area.


Subject(s)
Betacoronavirus , Consumer Health Informatics , Coronavirus Infections/epidemiology , Disease Outbreaks/statistics & numerical data , Pneumonia, Viral/epidemiology , User-Computer Interface , COVID-19 , Centers for Disease Control and Prevention, U.S. , Cities , Coronavirus Infections/mortality , Humans , Pandemics , Pneumonia, Viral/mortality , SARS-CoV-2 , Software , United States/epidemiology
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