WoLF PSORT Protein Localization
Predicts subcellular localization sites from protein sequence.
WoLF PSORT is an enhanced protein subcellular location prediction model based on amino acid sequences. It utilizes sorting signals, amino acid composition, and functional motifs to generate numerical localization features. These features are then used by a k-nearest neighbor classifier for predictions.
Estimated resource cost: 0.000031
Categories: Sequence Analysis & Annotation
Tags: Protein Localization Proteins
Key Capabilities
- Uses a modied kNN algorithm to predict the location of protein sequences.
- Designed for multi-kingdom use: animal, plant, fungi.
- Converts protein amino acid sequences into numerical localization features, incorporating sorting signals, amino acid composition, and functional motifs, such as DNA-binding motifs, for robust predictions.
- Utilizes a straightforward k-nearest neighbor (kNN) classifier for efficient and reliable subcellular location predictions.
- Offers users the ability to gain insights into the basis of predictions, helping them assess the reliability of predictions for specific proteins.
Runtime Statistics
| Metric | Value |
|---|---|
| runtime_mean | 5 |
| runtime_median | 4 |
| runtime_std | 7 |
| runtime_90th_percentile | 8 |
| runtime_max | 141 |
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Estimated Credits: 0.000031
Invite-only, limited-time access. Please contact ztang@getantibody.com.
Invite-only, limited-time access. Please contact ztang@getantibody.com.