DeepViscosity
Predict high-concentration monoclonal antibody viscosity classes.
DeepViscosity is an ensemble deep learning ANN model developed to predict high-concentration monoclonal antibody viscosity classes (Low <= 20 cP, High > 20 cP). The model utilized 30 spatial properties (descriptors) obtained from DeepSP surrogate model as features for training.
Estimated resource cost: 0.000062
Categories: Protein Design
Tags: Antibodies Developability Proteins Viscosity
Key Capabilities
- Predicts viscosity class (Low <= 20 cP, High > 20 cP) for monoclonal antibodies.
- Uses ensemble deep learning ANN model.
- Utilizes 30 spatial properties from DeepSP surrogate model.
Runtime Statistics
| Metric | Value |
|---|---|
| runtime_mean | 17 |
| runtime_median | 17 |
| runtime_std | 1 |
| runtime_90th_percentile | 19 |
| runtime_max | 22 |
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Ready to submit your job?
Review your configuration, then confirm the estimated credit cost before you run the job. Note that credit estimates are not guaranteed and runtime can vary depending on inputs and settings.
Estimated Credits: 0.000062
Invite-only, limited-time access. Please contact ztang@getantibody.com.
Invite-only, limited-time access. Please contact ztang@getantibody.com.