Dataset Search

Data from an a field survey at Nikko National Park in central Japan. Data contain information about deer carcass, environment of sites, and vertebrate scavenging.

Dataset associated with Allen et al. (In Review): Food caching by a solitary large carnivore supports optimal foraging theory If using this dataset, please cite this manuscript.

This data set includes all of data related to strain-resilient FETs based on 2D heterostructures including optical images of FETs, Raman characteristics data, Transport measurement data, and AFM topography data.

This dataset includes early embryogenesis and post-embryonic development of Soybean cyst nematode.

This dataset contains collected and aggregated network information from NCSA’s Blue Waters system, which is comprised of 27,648 nodes connected via Cray Gemini* 3D torus (dimension 24x24x24) interconnect, from Jan/01/2017 to May/31/2017. Network performance counters for links are exposed via Cray's gpcdr (<a href="https://github.com/ovis-hpc/ovis/wiki/gpcdr-kernel-module">https://github.com/ovis-hpc/ovis/wiki/gpcdr-kernel-module</a>) kernel module. Lightweight Distributed Metric Service ([LDMS](<a href="https://github.com/ovis-hpc/ovis">https://github.com/ovis-hpc/ovis</a>)) is used to sampled the performance counters at 60 second intervals. Please read "README.md" file. <b>Acknowledgement:</b> This dataset is collected as a part of the Blue Waters sustained-petascale computing project, which is supported by the National Science Foundation and the state of Illinois. Blue Waters is a joint effort of the University of Illinois at Urbana-Champaign and its National Center for Supercomputing Applications.

Mist netting data for little brown bats (Myotis lucifugus) in McHenry County, Illinois and output of acoustic data processed using Kaleidoscope (Version 5.1.9, Bats of North America 5.1.0; Wildlife Acoustics) auto-identification software. Associated survey metadata and landcover metrics calculated using Fragstats included.

This dataset is the numerical simulation data of the computational study of the cold front-related hydrodynamics in the Wax Lake delta. The numerical model used is ECOM-si.

GBS data from biparental sorghum populations provided by Dr. Bill Rooney, TAMU. Data produced and analyzed by Pradeep Hirannaiah to study recombination in sorghum. Funding for this study was provided by the Sorghum Checkoff.

This is a sample 5 minute video of an E coli bacterium swimming in a microfluidic chamber as well as some supplementary code files to be used with the Matlab code available at https://github.com/dfraebel/CellTracking

Monthly water withdrawal records (total pumpage and per-capita consumption) for the City of Austin, Texas (2000-2014). Data were provided by Austin Water Utility.

This is the data set associated with the manuscript titled "Extensive host-switching of avian feather lice following the Cretaceous-Paleogene mass extinction event." Included are the gene alignments used for phylogenetic analyses and the cophylogenetic input files.

This dataset includes both meteorology and oceanography data collected at stations (CSI03, CSI06, and CSI09) near the Gulf of Mexico from the LSU WAVCIS (Waves-Current-Surge Information System) lab. The associated data analysis visualization is also saved in separate directories.

This dataset is the field measurements of water depth at the Wax Lake delta conducted in late 2012.

Spire angle data for sinistral whelks of the family Busyconidae. Data focuses on spire angles, with some data on total shell length. Locality information is present for all modern specimens.

This dataset includes the data from an analysis of bobcat harvest data with particular focus on the relationship between catch-per-unit-effort and population size. The data relate to bobcat trapper and hunter harvest metrics from Wisconsin and include two RDS files which can be open in the software R using the readRDS() function.

This dataset contains 1 CSV file: RozanskyLarsonTaylorMsat.csv which contains microsatellite fragment lengths for Virile and Spothanded Crayfish from the Current River watershed of Missouri, U.S., and complimentary data, including assignments to species by phenotype and COI sequence data, GenBank accession numbers for COI sequence data, study sites with dates of collection and geographic coordinates, and Illinois Natural History Survey (INHS) Crustacean Collection lots where specimens are stored.

This data set includes survey responses collected during 2015 from academic libraries with library publishing services. Each institution responded to questions related to its use of user studies or information about readers in order to shape digital publication design, formats, and interfaces. Survey data was supplemented with institutional categories to facilitate comparison across institutional types.

This dataset is the field measurements of currents at two stations (Big Hogs Bayou and Delta1) in the the Wax Lake delta in November 2012 and February 2013.

This dataset includes data of the the Wax Lake delta from four public agencies: NGDC, USGS, NDBC, and NOAA CO-OPS. Besides the original data, the processed data associated with analyzed figures are also shared.

This dataset contains BEPAM model code and input data to replicate the outcomes for "The Economic and Environmental Costs and Benefits of the Renewable Fuel Standard". The dataset consists of: (1) The replication codes and data for the BEPAM model. The code file is named as output.gms. (BEPAM-Social cost model-ERL.zip) (2) Simulation results from the BEPAM model (BEPAM_Simulation_Results.csv) * Item (1) is in GAMS format. Item (2) is in text format.

#Overview These are reference packages for the TIPP3 software for abundance profiling and/or species detection from metagenomic reads (e.g., Illumina, PacBio, Nanopore, etc.). Different refpkg versions are listed. TIPP3 software: https://github.com/c5shen/TIPP3 #Changelog V1.2 (`tipp3-refpkg-1-2.zip`) >>Fixed old typos in the file mapping text. >>Added new files `taxonomy/species_to_marker.tsv` for new function `run_tipp3.py detection [...parameters]`. Please use the latest release of the TIPP3 software for this new function. V1 (`tipp3-refpkg.zip`) >>Initial release of the TIPP3 reference package. #Usage 1. unzip the file to a local directory (will get a folder named "tipp3-refpkg"). 2. use with TIPP3 software: `run_tipp3.py -r [path/to/tipp3-refpkg] [other parameters]`

GBS data from soybean lines carrying introgressions from Glycine tomentella. This project is led by Dr. Randy Nelson, USDA scientist at the University of Illinois. Fastq files contain raw Illumina data. Txt files are keyfiles containing barcodes for each genetic entity.

Datasets used in the study, "OCTAL: Optimal Completion of Gene Trees in Polynomial Time," under review at Algorithms for Molecular Biology. Note: DS_STORE file in 25gen-10M folder can be disregarded.

File Name: WordsSelectedByInformationGain.csv Data Preparation: Xiaoru Dong, Linh Hoang Date of Preparation: 2018-12-12 Data Contributions: Jingyi Xie, Xiaoru Dong, Linh Hoang Data Source: Cochrane systematic reviews published up to January 3, 2018 by 52 different Cochrane groups in 8 Cochrane group networks. Associated Manuscript authors: Xiaoru Dong, Jingyi Xie, Linh Hoang, and Jodi Schneider. Associated Manuscript, Working title: Machine classification of inclusion criteria from Cochrane systematic reviews. Description: the file contains a list of 1655 informative words selected by applying information gain feature selection strategy. Information gain is one of the methods commonly used for feature selection, which tells us how many bits of information the presence of the word are helpful for us to predict the classes, and can be computed in a specific formula [Jurafsky D, Martin JH. Speech and language processing. London: Pearson; 2014 Dec 30].We ran Information Gain feature selection on Weka -- a machine learning tool. Notes: In order to reproduce the data in this file, please get the code of the project published on GitHub at: https://github.com/XiaoruDong/InclusionCriteria and run the code following the instruction provided.