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Tabulated statistics of road networks at the level of intersections and for built-up areas for each decade from 1900 to 2010, and for 2015, for each core-based statistical area (CBSA, i.e., metropolitan and micropolitan statistical area) in the conterminous United States. These areas are derived from historical road networks developed by Johannes Uhl. See Burghardt et al. (2022) for details on the data processing. Spatial coverage: all CBSAs that are covered by the HISDAC-US historical settlement layers. This dataset includes around 2,700 U.S. counties. In the remaining counties, construction year coverage in the underlying ZTRAX data (Zillow Transaction and Assessment Dataset) is low. See Uhl et al. (2021) for details. All data created by Keith A. Burghardt, USC Information Sciences Institute, USA Codebook: these CBSA statistics are stratified by degree of aggregation. - CBSA_stats_diffFrom1950: Change in CBSA-aggregated patch statistics between 1950 and 2015 - CBSA_stats_by_decade: CBSA-aggregated patch statistics for each decade from 1900-2010 plus 2015 - CBSA_stats_by_decade: CBSA-aggregated cumulative patch statistics for each decade from 1900-2010 plus 2015. All roads created up to a given decade are used for calculating statistics. - Patch_stats_by_decade: Individual patch statistics for each decade from 1900-2010 plus 2015 - Patch_stats_by_decade: Individual cumulative patch statistics for each decade from 1900-2010 plus 2015. All roads created up to a given decade are used for calculating statistics. The statistics are the following: msaid: CBSA codeid: (if patch statistics) arbitrary int unique to each patch within the CBSA that yearyear: year of statisticspop: population within all CBSA countiespatch_bupr: built up property records (BUPR) within a patch (or sum of patches within CBSA)patch_bupl: built up property l (BUPL) within a patch (or sum of patches within CBSA)patch_bua: built up area (BUA) within a patch (or sum of patches within CBSA)all_bupr: Same as above but for all data in 2015 regardless of whether properties were in patchesall_bupl: Same as above but for all data in 2015 regardless of whether properties were in patchesall_bua: Same as above but for all data in 2015 regardless of whether properties were in patchesnum_nodes: number of nodes (intersections)num_edges: number of edges (roads between intersections)distance: total road length in kmk_mean: mean number of undirected roads per intersectionk1: fraction of nodes with degree 1k4plus: fraction of nodes with degree 4+bearing: histogram of different bearings between intersectionsentropy: entropy of bearing histogrammean_local_gridness: Griddedness used in textmean_local_gridness_max: Same as griddedness used in text but assumes we can have up to 3 quadrilaterals for degree 3 (maximum possible, although intersections will not necessarily create right angles) Code available at https://github.com/johannesuhl/USRoadNetworkEvolution. References: Burghardt, K., Uhl, J., Lerman, K., & Leyk, S. (2022). Road Network Evolution in the Urban and Rural United States Since 1900. Computers, Environment and Urban Systems.
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Predicting small molecule binding pockets on diacylglycerol kinases using chemoproteomics and AlphaFold
We provide a family-wide assessment of accessible sites for covalent targeting that combined with AlphaFold revealed predicted small molecule binding pockets for guiding future inhibitor development of the DGK superfamily.
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- Award ID(s):
- 2422750
- PAR ID:
- 10506256
- Publisher / Repository:
- the Royal Society of Chemistry
- Date Published:
- Journal Name:
- RSC Chemical Biology
- Volume:
- 4
- Issue:
- 6
- ISSN:
- 2633-0679
- Page Range / eLocation ID:
- 422 to 430
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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