127,591 to 127,600 of 128,240 Results
Jun 1, 2020 - Glycoside Hydrolase 19 Engineering Database
Orlando, Marco, 2020, "GraphML files for protein sequence networks of glycoside hydrolase 19 homologues", https://doi.org/10.18419/DARUS-802, DaRUS, V1
GraphML files for undirected weighted graphs with nodes that represent protein sequences of glycoside hydrolase 19 homologues. Protein sequences were clustered by a threshold of 90% sequence identity to derive representative sequences. Pairwise sequence identity between two sequences was derived from global Needleman-Wunsch alignment. Protein seque... |
GraphML Network Data - 14.3 MB -
MD5: a314980fa659092d23cfda60fb45929a
Protein sequence network for the chitinase domains from the Glycoside Hydrolase 19 Engineering Database.
The GraphML file contains representative nodes (clustered by 90% in USEARCH) connected by at least 60% pairwise sequence identity (edge weights derived from Needleman-Wunsch alignments). |
GraphML Network Data - 5.6 MB -
MD5: f255b9e12d219a65533643ae3b529282
Protein sequence network for the endolysin domains from the Glycoside Hydrolase 19 Engineering Database.
The GraphML file contains representative nodes (clustered by 90% in USEARCH) connected by at least 60% pairwise sequence identity (edge weights derived from Needleman-Wunsch alignments). |
GraphML Network Data - 72.1 MB -
MD5: 1ef54be08ab8b4dbe1f5b4a0407fac75
Protein sequence network for representative GH19 domains (corresponding to Pfam’s GH19 profile HMM: PF00182) from the Glycoside Hydrolase 19 Engineering Database. The GraphML file contains representative nodes (clustered by 90% in USEARCH) connected by at least 40% pairwise sequence identity (edge weights derived from Needleman-Wunsch alignments). |
May 28, 2020 - SFB-TRR 161 A02 "Quantifying Visual Computing Systems"
Bruder, Valentin; Müller, Christoph; Frey, Steffen; Ertl, Thomas, 2020, "Runtime performance measurements of interactive visualisation algorithms", https://doi.org/10.18419/DARUS-810, DaRUS, V1
Runtime performance measurements for GPU-based direct volume rendering and GPU-based raycasting of spherical particles on ten different discrete graphics processing units from AMD and NVIDIA. The data set at hand systematically evaluates typical factors influencing performance of interactive visualisations like view-port size, data set size, camera... |
PNG Image - 668.2 KB -
MD5: a3e7399fe3a20c80bfba9e0c4483cc06
Sample rendering of the "bat.dat" data set, |
PNG Image - 365.6 KB -
MD5: 961e874a3ddb5afc0a33bca1c5c4eab4
Sample rendering of the "bonsai.dat" data set. |
PNG Image - 416.5 KB -
MD5: 47baea9a0693437950b3d0434c63de4e
Sample rendering of the "bunny.dat" data set. |
PNG Image - 755.9 KB -
MD5: 2fc4fd894d55d9cec4e529f0b97a11e1
Sample rendering of the "chameleon.dat" data set. |
PNG Image - 535.9 KB -
MD5: dacdc0f05bbeaf0878d846e4cac6c659
Sample rendering of the "engine.dat" data set. |
