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README.md
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---
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license: mit
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---
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# Dataset Description
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## Dataset Summary
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This dataset was derived from the Stanford HIV Genotype-Phenotype database and contains 1,733 HIV protease sequences. A
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pproximately half of the sequences are resistant to at least one antiretroviral therapeutic (ART).
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Supported Tasks and Leaderboards: None
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Languages: English
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## Dataset Structure
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### Data Instances
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Each column represents the protein amino acid sequence of the HIV protease protein. The ID field indicates the Genbank reference ID for future cross-referencing. There are 1,733 total protease sequences.
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Data Fields: ID, sequence, fold, FPV, IDV, NFV, SQV
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Data Splits: None
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## Dataset Creation
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Curation Rationale: This dataset was curated to train a model (HIV-BERT-PI) designed to predict whether an HIV protease sequence would result in resistance to certain antiretroviral (ART) drugs.
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Initial Data Collection and Normalization: Dataset was downloaded and curated on 12/21/2021.
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## Considerations for Using the Data
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Social Impact of Dataset: Due to the tendency of HIV to mutate, drug resistance is a common issue when attempting to treat those infected with HIV.
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Protease inhibitors are a class of drugs that HIV is known to develop resistance via mutations.
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Thus, by providing a collection of protease sequences known to be resistant to one or more drugs, this dataset provides a significant collection of data that could be utilized to perform computational analysis of protease resistance mutations.
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Discussion of Biases: Due to the sampling nature of this database, it is predominantly composed of subtype B sequences from North America and Europe with only minor contributions of Subtype C, A, and D.
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Currently, there was no effort made to balance the performance across these classes.
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As such, one should consider refinement with additional sequences to perform well on non-B sequences.
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## Additional Information:
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- Dataset Curators: Will Dampier
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- Citation Information: TBA
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---
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license: mit
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---
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