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...
Last updated on 2023-03-21T18:35:22+00:00 by LN Anderson SAGE-RTP RT-PCR Amplicon Sequencing Barcode Count Analysis Promoter expression data for five bacterial species associated with the Serine recombinase Assisted Genome Engineering (SAGE) research project. Raw Measurement Data NCBI BioProject...
Elmore JR, Dexter GN, Baldino H, Huenemann JD, Francis R, Peabody GL 5th, Martinez-Baird J, Riley LA, Simmons T, Coleman-Derr D, Guss AM, Egbert RG. High-throughput genetic engineering of nonmodel and undomesticated bacteria via iterative site-specific genome integration. Sci Adv. 2023 Mar 10;9(10)...
Last updated on 2023-02-23T19:37:46+00:00 by LN Anderson Snekmer: A scalable pipeline for protein sequence fingerprinting using amino acid recoding (AAR) Snekmer is a software package designed to reduce the representation of protein sequences by combining amino acid reduction (AAR) with the kmer...
Christine H Chang, William C Nelson, Abby Jerger, Aaron T Wright, Robert G Egbert, Jason E McDermott, Snekmer: a scalable pipeline for protein sequence fingerprinting based on amino acid recoding, Bioinformatics Advances , Volume 3, Issue 1, 2023, vbad005, https://doi.org/10.1093/bioadv/vbad005...
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...
Please cite as : McClure R.S., Y. Farris, R.E. Danczak, W.C. Nelson, H. Song, A. Kessler, and J. Lee, et al. 2022. 16s data from MSC-2 growth. [Data Set] PNNL DataHub. https://data.pnnl.gov/group/nodes/dataset/33231 16s data from MSC-2 growth 3 fastq of 16s amplicon data of MSC2 1 csv file of raw...
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...
"Visualizing the Hidden Half: Plant-Microbe Interactions in the Rhizosphere" Plant roots and the associated rhizosphere constitute a dynamic environment that fosters numerous intra- and interkingdom interactions, including metabolite exchange between plants and soil mediated by root exudates and the...
Pending Review Microbiomes contribute to multiple ecosystem services by transforming organic matter in soil. Extreme shifts in the environment, such as drying-rewetting cycles during drought, can impact microbial metabolism of organic matter by altering their physiology and function. These...
ProxyTSPRD profiles are collected using NVIDIA Nsight Systems version 2020.3.2.6-87e152c and capture computational patterns from training deep learning-based time-series proxy-applications on four different levels: models (Long short-term Memory and Convolutional Neural Network), DL frameworks...
This data set provides the 16S microbial community composition via DNA sequence analysis from ingrowth peat and sand cores at the South End bog in 2013. These samples were collected outside the experimental enclosures and are pre-treatment with no experimental manipulation. These are part of the...
