The Human Islet Research Network (HIRN) is a large consortia with many research projects focused on understanding how beta cells are lost in type 1 diabetics (T1D) with a goal of finding how to protect against or replace the loss of functional beta cells. The consortia has multiple branches of...
The Phenotypic Response of the Soil Microbiome to Environmental Perturbations Project (Soil Microbiome SFA) at Pacific Northwest National Laboratory is a Genomic Sciences Program Science Focus Area (SFA) Project operating under the Environmental Microbiome Science Research Area. The Soil Microbiome...
Spruce and Peatlands Responses Under Changing Environments (SPRUCE) site is the 8.1-ha S1 bog, a Picea mariana [black spruce] – Sphagnum spp. ombrotrophic bog forest in northern Minnesota, 40 km north of Grand Rapids, in the USDA Forest Service Marcell Experimental Forest (MEF). Two field research...
Last updated on 2023-02-23T19:37:46+00:00 by LN Anderson PerCon SFA Project Publication Experimental Data Catalog The Persistence Control of Engineered Functions in Complex Soil Microbiomes Project (PerCon SFA) at Pacific Northwest National Laboratory ( PNNL ) is a Genomic Sciences Program...
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...
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...
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...
Predictive Phenomics is addressing the grand challenge of understanding and predicting phenotype by identifying the molecular basis of function and enable function-driven design and control of biological systems .
Dataset The dataset will consist of: About 1200 news stories from the Alderwood Daily News plus a few other items collected by the previous investigators A few photos A few maps of Alderwood and vicinity (in bitmap image form) A few files with other mixed materials, e.g. a spreadsheet with voter...
It is Fall of 2004 and one of your analyst colleagues has been called away from her current tasks to an emergency. The boss has given you the assignment of picking up her investigation and completing her task. She has been asked to pursue a line of investigation into some unexpected activities...
Mini Challenge 1: Wiki Editors The Paraiso movement is controversial and is having considerable social impact in a specific area of the world. We have extracted a segment of the Paraiso (the movement) Wikipedia edits page. Please note this is not the Paraiso Manifesto Wiki page which is part of the...
The VAST 2009 Challenge scenario concerned a fictitious, cyber security event. An employee leaked important information from an embassy to a criminal organization. Participants were asked to discover the identity ofthe employee and the structure of the criminal organization. Participants were...
The VAST 2010 Challenge consisted of three mini-challenges (MC) and one Grand Challenge (GC). Each MC had a data set, instructions and a number of questions to be answered. The GC required participants to pull together information from all three data sets and write a debrief summarizing the...
This year’s VAST Challenge focuses on visual analytics applications for both large scale situation analysis and cyber security. We have two mini-challenges to test your analytical skills and confound your visual analytics applications. In the first mini-challenge, (the imaginary) BankWorld's largest...