Published August 28, 2023
| Version v1
Dataset
Open
Machine learning-guided high throughput nanoparticle design
Creators
- 1. Eindhoven University of Technology
Description
Widefield microscopy high content images used for this study. Contains all the intermediate reports in excel result from image analysis and processing:
- 00_Initial Dataset (DoE): contains all image data used to determine the labels for the first active learning cycle. Nano particle formulations were suggested using deisgn of experiments.
- 01_ML_Iteration01 (Exploration): contains all image data used to determine the labels for the formulations suggested by the first active learning cycle
- 02_ML_Iteration02 (Exploitation): contains all image data used to determine the labels for the formulations suggested by the second active learning cycle
- 03_ML_Iteration03 (Exploration): contains all image data used to determine the labels for last (model validation) experiment. Includes the subsets of particles predicted with low and high uptake.
Files
Ortiz-Perez_2023_all_data.zip
Files
(9.8 GB)
Name | Size | Download all |
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md5:58d1cac18aa4fbafd44bd97323406d0c
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9.8 GB | Preview Download |
Additional details
Related works
- Is part of
- Preprint: 10.26434/chemrxiv-2023-sqb5c (DOI)
Software
- Repository URL
- https://github.com/molML/Nano_Particles_Active_Learning
- Development Status
- Active