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...

Coastal landscapes are increasingly exposed to seawater due to sea level rise and extreme weather events. The biogeochemical responses of these vulnerable ecosystems are poorly understood, limiting our ability to predict how their role in global biogeochemical cycles will shift under future...

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...

Sara Gosline received BA in Computer Science from Columbia University and spent two years working in software before returning to graduate school full time. She received her Masters and PhD in Computer Science from McGill University with a specialty in Bioinformatics and then moved to the...

Biography Kelly is a senior data scientist in the Computational Biology group within the Biological Sciences Division at Pacific Northwest National Laboratory (PNNL). After earning a MS in Biostatistics from the University of Washington in 2012, she worked at a cancer research company for two years...

David Degnan is a biological data scientist who develops bioinformatic and statistical pipelines for multi-omics data, specifically the fields of proteomics, metabolomics, and multi-omics (phenotypic) data integration. He has experience with top-down & bottom-up proteomics analysis, genomics &...

Stanford Synchrotron Radiation Lightsource Experimental Station 14-3b is a bending magnet side station dedicated to X-Ray Imaging and Micro X-Ray Absorption Spectroscopy of biological, biomedical, materials, and geological samples. Station 14-3b is equipped with specialized instrumentation for XRF...

Rigaku Rapid II Microbeam is one of the most versatile micro-diffraction XRD system in materials analysis, using advanced imaging plate technology for measuring diffraction patterns and diffuse scattering from a wide range of materials. The RAPID™ II Curved Detector X-Ray Diffraction (XRD) System's...

The EyeSea underwater video dataset was assembled for developing algorithms for detecting fish in real world underwater video data. The data were recorded as part of environmental monitoring efforts at three different water power sites. The Ocean Renewable Power Company (ORPC) data were recorded in...

The year 2014 solution files are based on model calibration effort based on inputs and data from Year 2014 as described in Khangaonkar et al. 2018). It includes water surface elevation, currents, temperature and salinity at an hourly interval. These netcdf files with 24 hourly records include...

The year 2014 solution files are based on model calibration effort based on inputs and data from Year 2014 as described in Khangaonkar et al. 2018). It includes water surface elevation, currents, temperature and salinity at an hourly interval. These netcdf files with 24 hourly records include...

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 dataset presents land surface parameters designed explicitly for global kilometer-scale Earth system modeling and has significant implications for enhancing our understanding of water, carbon, and energy cycles in the context of global change. Specifically, it includes four categories of...