metadata
license: mit
Description
Fluorescence prediction is a regression task where each input protein x is mapped to a label y ∈ R, corresponding to the log-fluorescence intensity of x.
Splits
Structure type: None
The dataset is from Evaluating Protein Transfer Learning with TAPE. We follow the original data splits, with the number of training, validation and test set shown below:
- Train: 20963
- Valid: 5235
- Test: 25517
Data example
We organize all data in LMDB format. Below are examples in the dataset to show how data is organized:
| Key | seq | fitness |
|---|---|---|
| 0 | S#K#G#E#E#L#F#T#G#V#V#P#I#L#V#E#L#D#G#D#V#N#G#H#K#F#S#V#S#G#E#G#E#G#D#A#T#Y#G#K#L#T#L#K#F#I#C#T#T#G#K#L#P#V#P#W#P#T#L#V#T#T#L#S#Y#G#V#Q#C#F#S#R#Y#P#D#H#M#K#Q#H#D#F#F#K#S#A#M#P#E#G#Y#V#Q#E#R#T#I#F#F#K#D#D#G#N#Y#K#T#R#A#E#V#K#F#E#G#D#T#L#V#N#R#I#E#L#K#G#I#D#F#K#E#D#G#N#I#L#G#H#K#L#E#Y#N#Y#N#S#H#N#V#Y#I#M#A#D#K#Q#K#N#G#I#K#V#N#F#K#I#R#H#K#I#E#D#G#S#V#Q#L#A#D#H#Y#Q#Q#N#T#P#I#G#D#G#P#V#L#L#P#D#N#H#Y#L#S#T#Q#S#A#L#S#K#D#P#N#E#K#R#D#H#M#V#L#L#E#F#V#T#A#A#G#I#T#H#G#M#D#E#R#Y#K# | 3.8237006664276123 |
| 1 | S#K#G#E#E#L#F#T#G#V#V#P#I#L#V#E#L#D#G#D#V#N#G#H#K#F#S#V#S#G#E#G#E#G#D#A#T#Y#G#K#L#T#L#K#F#I#C#T#T#G#R#L#P#V#P#W#P#T#L#V#T#T#L#S#Y#G#A#Q#C#F#S#R#Y#P#D#H#M#K#Q#H#D#F#F#K#S#A#M#P#E#G#Y#V#Q#E#R#T#I#F#F#K#D#D#G#N#Y#K#T#R#A#E#V#K#F#E#G#D#T#L#V#N#R#I#E#L#K#G#I#D#F#K#E#D#G#N#I#L#G#H#K#L#E#Y#N#Y#N#S#H#N#V#Y#I#M#A#D#K#Q#K#N#G#I#K#V#N#F#K#I#R#H#N#I#E#D#G#S#V#Q#L#A#D#H#Y#Q#Q#N#T#P#I#G#D#G#P#V#L#L#P#D#N#H#Y#L#S#T#Q#S#A#L#S#K#D#P#N#E#K#R#D#H#M#V#L#L#E#F#V#T#A#A#G#I#T#H#G#M#D#E#L#Y#K# | 3.7520840167999268 |
| 2 | S#K#G#E#E#L#F#T#G#V#V#P#I#L#V#E#L#D#G#D#V#N#G#H#K#F#S#V#S#G#E#G#E#G#D#A#T#Y#G#K#L#T#L#K#F#I#C#T#T#G#K#L#P#V#P#W#P#T#L#V#T#T#L#S#Y#G#V#Q#C#F#S#R#Y#P#D#H#M#K#Q#H#D#F#F#K#S#A#M#P#E#G#Y#V#Q#E#R#T#I#F#F#K#D#D#G#N#Y#K#T#R#A#E#V#K#F#E#G#D#T#L#V#N#R#I#E#L#K#G#I#D#F#K#E#D#G#N#I#L#G#H#K#L#E#Y#N#Y#N#S#H#N#V#Y#I#M#A#D#K#Q#K#N#G#I#K#V#N#F#K#I#R#H#N#I#E#D#G#S#V#Q#L#A#D#H#Y#Q#Q#N#T#P#I#G#D#G#P#V#L#L#P#D#N#H#Y#L#S#A#Q#S#A#L#S#K#D#P#N#E#K#R#D#H#M#V#L#L#E#F#V#T#A#A#G#I#T#L#G#M#D#E#L#Y#K# | 3.540156364440918 |
Here Key is the index and remaining columns are stored in a dictionary, e.g. "0" -> {"seq": xxx, "fitness": xxx}.