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11 to 20 of 1,292 Results
ZNB.xml
Apr 28, 2025 - MD Simulations with PRDM9
XML - 1.6 KB - MD5: a8f183de30b9a05bd6a6515d639ea88c
Parameter file for zinc ions
raw_data.zip
Jan 13, 2025 - NGS data related to Sogl et al. "Specificities and flanking sequence preferences of bacterial DNA-(cytosine C5)-methyltransferases"
ZIP Archive - 177.1 MB - MD5: 6e0120fb5866aaffd82db1fbfa76b252
readme-1.pdf
readme-1.pdf
Jan 13, 2025 - NGS data related to Sogl et al. "Specificities and flanking sequence preferences of bacterial DNA-(cytosine C5)-methyltransferases"
Adobe PDF - 104.6 KB - MD5: 1fa8ecab0ba68b617138a98d90160ffc
Description of the data structure
source_data.xlsx
Jan 13, 2025 - NGS data related to Sogl et al. "Specificities and flanking sequence preferences of bacterial DNA-(cytosine C5)-methyltransferases"
MS Excel Spreadsheet - 736.2 KB - MD5: ddd9a622dbb5638621ca557e01fc4ec2
Supplementary_Table_S1.tab
Jan 13, 2025 - NGS data related to Sogl et al. "Specificities and flanking sequence preferences of bacterial DNA-(cytosine C5)-methyltransferases"
Tabular Data - 53.3 KB - 8 Variables, 1106 Observations - UNF:6:bSvQoJxvb+T/iyQGPOvTBA==
Assignment of experiments and data files and overview of the number of reads in CSV format
Supplementary Table S1.xlsx
Jan 13, 2025 - NGS data related to Sogl et al. "Specificities and flanking sequence preferences of bacterial DNA-(cytosine C5)-methyltransferases"
MS Excel Spreadsheet - 56.4 KB - MD5: a3df4453d1eb9612fabd87027482cfbe
Assignment of experiments and data files and overview of the number of reads
1_data_retrival.ipynb
Nov 27, 2024 - Data related to Panzer: A Machine Learning Based Approach to Analyze Supersecondary Structures of Proteins
Jupyter Notebook - 3.5 KB - MD5: 5aed17f7e8f45b9c585d0fdfc2d3abe1
2_data_storage_and_embeddings.ipynb
Nov 27, 2024 - Data related to Panzer: A Machine Learning Based Approach to Analyze Supersecondary Structures of Proteins
Jupyter Notebook - 32.7 KB - MD5: 23d1c66d472cef8df61d1b4af946e138
3_data_science.ipynb
Nov 27, 2024 - Data related to Panzer: A Machine Learning Based Approach to Analyze Supersecondary Structures of Proteins
Jupyter Notebook - 15.3 KB - MD5: c9d86d81c81d45f0e504062f1a790448
fastas.zip
Nov 27, 2024 - Data related to Panzer: A Machine Learning Based Approach to Analyze Supersecondary Structures of Proteins
ZIP Archive - 222.7 MB - MD5: fff77ced43a39c8357ea141bd0b9fda8
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