Designing Vaccines that Are Robust to Virus Escape
Authors: Swetasudha Panda, Yevgeniy Vorobeychik
AAAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We demonstrate the effectiveness of the proposed methods, and exhibit an antibody with a far higher escape cost (7) than the native (1). |
| Researcher Affiliation | Academia | Swetasudha Panda and Yevgeniy Vorobeychik Electrical Engineering and Computer Science Vanderbilt University, Nashville, TN swetasudha.panda@vanderbilt.edu, yevgeniy.vorobeychik@vanderbilt.edu |
| Pseudocode | No | The paper does not include structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper provides Google Drive links for "Elaborated information on this research" but does not explicitly state that these links contain the source code for the methodology. |
| Open Datasets | No | To evaluate our approach we used a native antibody-virus interaction for HIV. The native structure is the co-crystal structure of the antibody VRC01 complexed with the HIV envelope protein GP120. The paper describes the data source but does not provide concrete access information (link, DOI, specific repository, or citation to a publicly available dataset) for it. |
| Dataset Splits | No | The paper does not provide specific train/validation/test dataset splits, percentages, or sample counts. |
| Hardware Specification | No | The paper does not specify any particular hardware details (e.g., GPU/CPU models, memory) used for running the experiments. |
| Software Dependencies | No | The paper mentions using "Rosetta" as a computational protein modeling tool but does not provide its version number or any other software dependencies with specific version information. |
| Experiment Setup | No | The paper describes the methods used but does not provide specific experimental setup details such as hyperparameter values, model initialization, or training schedules. |