35 Works

Spreadsheet of Data

Brown adipose tissue (BAT) is a fat tissue present in most mammals, which is specialized in non-shivering thermogenesis. Thermogenic activity in BAT is commonly detected by PET/CT imaging with 18F-FDG, a glucose analog, in both rodents and humans. Increased uptake of the 18F-FDG within regions of BAT is interpreted as an indicator of increased thermogenic activity within the tissue. Despite its prevalence, recent studies have begun to question the use of 18F-FDG PET/CT for the...

Session Laws Passed by the North Carolina General Assembly During 1866/67-1967 (plain text format) version 1

Matt Jansen, Neil Byers, Amanda Henley, Rucha Dalwadi & Lorin Bruckner
This corpus was created for a text analysis project called On the Books: Jim Crow and Algorithms of Resistance. On the Books focused specifically on the laws passed during the Jim Crow Era, which is defined for this project as the period between Reconstruction and the Civil Rights Movement (1866-1967). This dataset contains 96 text files, one for each volume in the corpus, in a plain text format. This work is licensed under a Creative...

DOE Project Data Archive

This is the data archive for the DOE project. It is fully public accessible. For questions please contact Jason Surratt: surratt@unc.edu.

Animal 770

Animal 770. Male, WT, Set 2 (w/ NE).

Data for Open Access Patterns in Emerging Scholars’ Journal Choice: A Bibliometric Analysis

This bibliometric analysis of University of North Carolina at Chapel Hill research provides a case study for tenure-track faculty’s open access publishing action. Looking specifically at the publications of 300 tenure-track assistant professors and instructors, this study creates a series of quantitative information visualizations to see researcher publishing trends leading up to tenure review. It identifies the proportion of assistant professors publishing open access, breaks down the top departments, and shows how open access has...

Animal 704 w/ NE

Animal 704. Male, KO, Set 2 (w/ NE).

Animal 704 w/o NE

Animal 704. Male, KO, Set 2 (w/o NE).

Animal 706 w/ NE

Animal 706. Male, KO, Set 2 (w/ NE).

Animal 706 w/o NE

Animal 706. Male, KO, Set 2 (w/o NE).

AFM data for Dynamic MutS-MuL complexes compact mismatched DNA

DNA mismatch repair (MMR) corrects errors that occur during DNA replication. In humans, mutations in the proteins MutS and MutL that initiate MMR cause Lynch Syndrome, the most common hereditary cancer. MutSα surveils the DNA, and upon recognition of a replication error, it undergoes ATP-dependent conformational changes and recruits MutLα. Subsequently PCNA activates MutL to nick the error-containing strand to allow excision and resynthesis. The structure-function properties of these obligate MutS-MutL complexes remain mostly unexplored...

Carbon Dioxide (CO2) Fluxes from Terrestrial and Aquatic Environments in a High-Altitude Tropical Catchment

Diego Riveros-Iregui, Andrew Murray, Keridwen Whitmore, Chloe Schneider, Megan Raisle & Maribel Herrara

Session Laws Passed by the North Carolina General Assembly during 1866/67-1967, Identified by Machine Learning as Laws Likely to be Jim Crow Laws (plain text format, single file) version 1

Lorin Bruckner, Rucha Dalwadi, William Sturkey, Matt Jansen, Amanda Henley, Kimber Thomas & Neil Byers
This corpus was created for a text analysis project called On the Books: Jim Crow and Algorithms of Resistance. On the Books focused specifically on the laws passed during the Jim Crow Era, which is defined for this project as the period between Reconstruction and the Civil Rights Movement (1866-1967). In addition to creating the corpus, the project also used machine learning to identify discoverable North Carolina segregation statutes during the Jim Crow era. This...

Animal 100

Animal 100. Female, KO, Set 1.

Animal 847

Animal 847. Male, WT, Set 1.

Animal 790 w/o NE

Animal 790. Male, KO, Set 2 (w/o NE).

Animal 80

Animal 80. Male, KO, Set 1.

Session Laws Passed by the North Carolina General Assembly During 1866/67-1967 (XML format) version 1

Neil Byers, Rucha Dalwadi, Kimber Thomas, Matt Jansen, William Sturkey, Lorin Bruckner & Amanda Henley
This corpus was created for a text analysis project called On the Books: Jim Crow and Algorithms of Resistance. On the Books focused specifically on the laws passed during the Jim Crow Era, which is defined for this project as the period between Reconstruction and the Civil Rights Movement (1866-1967). In addition to creating the corpus, the project also used machine learning to identify discoverable North Carolina segregation statutes during the Jim Crow era. This...

Animal 982

Animal 982. Female, WT, Set 1.

Animal 790 w/ NE

Animal 790. Male, KO, Set 2 (w/ NE).

Animal 72

Animal 72. Male, WT, Set 1.

Animal WT1 w/ NE

Animal WT1. Male, WT, Set 2 (w/ NE).

Animal WT1 w/o NE

Animal WT1. Male, WT, Set 2 (w/o NE).

Animal 70

Animal 70. Female, KO, Set 1.

AFM data for Dynamic MutS-MuL

AFM studies of the formation of human MutS-MutL mismatch repair initiation complexes. DNA mismatch repair (MMR) corrects errors that occur during DNA replication. In humans, mutations in the proteins MutS and MutL that initiate MMR cause Lynch Syndrome, the most common hereditary cancer. MutSα surveils the DNA, and upon recognition of a replication error, it undergoes ATP-dependent conformational changes and recruits MutLα. Subsequently PCNA activates MutL to nick the error-containing strand to allow excision and...

Session Laws Passed by the North Carolina General Assembly During 1866/67-1967, Identified by Machine Learning as Laws Likely to be Jim Crow Laws (XML format) version 1

Neil Byers, Amanda Henley, Kimber Thomas, Rucha Dalwadi, William Sturkey, Lorin Bruckner & Matt Jansen
This corpus was created for a text analysis project called On the Books: Jim Crow and Algorithms of Resistance. On the Books focused specifically on the laws passed during the Jim Crow Era, which is defined for this project as the period between Reconstruction and the Civil Rights Movement (1866-1967). In addition to creating the corpus, the project also used machine learning to identify discoverable North Carolina segregation statutes during the Jim Crow era. This...

Registration Year

  • 2020
    35

Resource Types

  • Dataset
    35

Affiliations

  • University of North Carolina at Chapel Hill
    2