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# Nanoparticle read across toxicity predictions with nano-lazar
# Requirements
- Nanoparticle characterisation
- Toxicity measurements
# eNanoMapper data import
Nanoparticles imported: 464
Nanoparticles with particle characterisation: 394
Nanoparticles with toxicity data: 167
Nanoparticles with toxicity data and particle characterisation: 160
# eNanoMapper toxicity endpoints
.. alles ohne falsch? zugewiesene protein corona tox endpoints
Toxicity endpoints: 41
Toxicity endpoints with more than one measurement value: 22
Toxicity endpoints with more than 10 measurements: 2
# Selected data
Protein corona dataset Au particles (106 particles)
Toxicity endpoint:
# Read across procedure
- Identify relevant fragments (significant correlation with toxicity)
TODO list of fragments, number
- Calculate similarities (weighted cosine similarity, correlation coefficients = weights)
- Identify neighbors (particles with more than 0.95 similarity)
- Calculate prediction (weighted average from neighbors, similarities = weights)
# Future development
- Validation of predictions
- Applicability domain/reliability of predictions
- Accuracy improvements:
- additional data
- feature selection
- similarity calculation
- predictions (local regression models)
- Usability improvements:
- additional data (extension of applicability domain, additional endpoints and chemistries)
- inclusion of ontologies
- Descriptor calculation directly from core and coating chemistries
# Webinterface
Your recommendations?
# Source code
https://github.com/opentox/nano-lazar
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