Dr. Gao obtained her Ph.D degree in Chemistry from institute of chemistry, Chinese Academy of Science. His Ph.D research focused on multiscale modeling of morphology and properties of polymeric materials, polymer processing and unveiling the process–properties relationships. (atomic to coarse...

Comprised of 6,426 sample runs, The Environmental Determinants of Diabetes in the Young (TEDDY) proteomics validation study constitutes one of the largest targeted proteomics studies in the literature to date. Making quality control (QC) and donor sample data available to researchers aligns with...

A total of 172 children from the DAISY study with multiple plasma samples collected over time, with up to 23 years of follow-up, were characterized via proteomics analysis. Of the children there were 40 controls and 132 cases. All 132 cases had measurements across time relative to IA. Sampling was...

Inclusion levels of alternative splicing (AS) events of five different varieties (i.e. skipped exon (SE), retained intron (RI), alternative 5’ splice site (A5SS), alternative 3’ splice site (A3SS), and mutually exclusive exons (MXE)) were measured in human blood samples from two separate cohorts of...

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 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...

Supporting data and code uploaded to DataHub for "How do the weather regimes drive wind speed and power production at the sub-seasonal to seasonal timescales over the CONUS?" Created by Ye Liu*, Sha Feng*, Yun Qian, Berg K Larry, Huilin Huang *POC: Ye Liu, Ye.Liu@pnnl.gov Sha Feng, sfeng@pnnl.gov --...