Deep phenotypic profiling of neuroactive drugs in larval zebrafish
The dataset accompanies the DeepFish manuscript "Deep phenotypic profiling of neuroactive drugs in larval zebrafish". It consists of motion index time-series data derived from 3 phenotypic screens: 1) SCREEN-WELL Neurotransmitter Set of 650 known drugs (NT650), 2) Quality control screen o...
Gespeichert in:
1. Verfasser: | |
---|---|
Format: | Dataset |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext bestellen |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | The dataset accompanies the DeepFish manuscript "Deep phenotypic profiling of neuroactive drugs in larval zebrafish". It consists of motion index time-series data derived from 3 phenotypic screens:
1) SCREEN-WELL Neurotransmitter Set of 650 known drugs (NT650), 2) Quality control screen of 16 known drugs (QC_Screen), and 3) ChemBridge DIVERSet Screening Library (10,000 compounds)
For each, we provide raw data files (in the form of zipped numpy arrays), and associated csv files with additional information, such as the name of the chemical and its location on the plate. The index of the row in the numpy arrays corresponds to the same index in the associated CSV files.
We also provide two saved PyTorch models from our manuscript: Twin-NN (twin-nn-saved-model-state-dict.pt.zip) and Twin-DN (twin-dn-saved-model-state-dict.pt.zip).
Finally we provide a dataset of prepared train and test pairs (as described in the manuscript) in 4 .npy arrays (pairs_train.npy, pairs_test.npy, labels_train.npy, labels_test.npy). These can be loaded by the code provided in the github repo and used to train models. |
---|---|
DOI: | 10.5281/zenodo.10652681 |