1,321 to 1,330 of 5,197 Results
Feb 3, 2025 - Coronavirus Neutralizing Antibodies
Rashid, Shamima; Wan, Zhang; Kwoh, Chee Keong; Lin, Zhuoyi; Ng, Shaun Yue Hao; Yin, Rui; Senthilnath, J., 2025, "Related Data for: PESI: Paratope-Epitope Set Interaction for SARS-CoV-2 Neutralization Prediction", https://doi.org/10.21979/N9/IZZKTZ, DR-NTU (Data), V1, UNF:6:XqxFQ/x98XTQs7+Ns8GGJw== [fileUNF]
This dataset contains 3 versions of epitope-paratope data and their neutralizing data for the SARS-CoV 2 virus. We pre-processed and annotated antibody-antigen binding data from the Observed Antibody Space (OAS) database to obtain these paratopes and epitopes. |
Feb 3, 2025 -
Related Data for: PESI: Paratope-Epitope Set Interaction for SARS-CoV-2 Neutralization Prediction
Plain Text - 281 B -
MD5: b6f4c46fb08d07a94449762ae037d9e1
Citation Information |
Feb 3, 2025 -
Related Data for: PESI: Paratope-Epitope Set Interaction for SARS-CoV-2 Neutralization Prediction
MS Excel Spreadsheet - 8.9 MB -
MD5: 2713a4b215b8c6a8429e44dc0d6f6342
Raw Data |
Feb 3, 2025 -
Related Data for: PESI: Paratope-Epitope Set Interaction for SARS-CoV-2 Neutralization Prediction
Tabular Data - 23.8 KB - 6 Variables, 310 Observations - UNF:6:1S8xNlxC/A5bjyz5wcJXPQ==
the data with PDB identifiers in columns |
Feb 3, 2025 -
Related Data for: PESI: Paratope-Epitope Set Interaction for SARS-CoV-2 Neutralization Prediction
Tabular Data - 21.3 KB - 5 Variables, 310 Observations - UNF:6:GtERqAvwJ8cPApagJMT+dg==
Pre-processed data |
Feb 3, 2025 -
Related Data for: PESI: Paratope-Epitope Set Interaction for SARS-CoV-2 Neutralization Prediction
Python Source Code - 762 B -
MD5: 892894b6ebf417b6fd4945ec00db732d
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Feb 3, 2025 -
Related Data for: PESI: Paratope-Epitope Set Interaction for SARS-CoV-2 Neutralization Prediction
Jupyter Notebook - 222.3 KB -
MD5: ed2bb96a02e866f3a3210f35e8e16cfa
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Feb 3, 2025 -
Related Data for: PESI: Paratope-Epitope Set Interaction for SARS-CoV-2 Neutralization Prediction
Markdown Text - 1.2 KB -
MD5: 75cc3591864d6e42ae9dbbf4daf859cd
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Jan 16, 2025 - S-Lab for Advanced Intelligence
Hu, Tao; Hong, Fangzhou; Liu, Ziwei, 2025, "SurMo: Surface-based 4D Motion Modeling for Dynamic Human Rendering (CVPR 2024)", https://doi.org/10.21979/N9/JDZOJE, DR-NTU (Data), V1
Dynamic human rendering from video sequences has achieved remarkable progress by formulating the rendering as a mapping from static poses to human images. However, existing methods focus on the human appearance reconstruction of every single frame while the temporal motion relati... |
