QSAR fish toxicity
Donated on 9/22/2019
Data set containing values for 6 attributes (molecular descriptors) of 908 chemicals used to predict quantitative acute aquatic toxicity towards the fish Pimephales promelas (fathead minnow).
Dataset Characteristics
Multivariate
Subject Area
Physics and Chemistry
Associated Tasks
Regression
Feature Type
Real
# Instances
908
# Features
-
Dataset Information
Additional Information
This dataset was used to develop quantitative regression QSAR models to predict acute aquatic toxicity towards the fish Pimephales promelas (fathead minnow) on a set of 908 chemicals. LC50 data, which is the concentration that causes death in 50% of test fish over a test duration of 96 hours, was used as model response. The model comprised 6 molecular descriptors: MLOGP (molecular properties), CIC0 (information indices), GATS1i (2D autocorrelations), NdssC (atom-type counts), NdsCH ((atom-type counts), SM1_Dz(Z) (2D matrix-based descriptors). Details can be found in the quoted reference: M. Cassotti, D. Ballabio, R. Todeschini, V. Consonni. A similarity-based QSAR model for predicting acute toxicity towards the fathead minnow (Pimephales promelas), SAR and QSAR in Environmental Research (2015), 26, 217-243; doi: 10.1080/1062936X.2015.1018938
Has Missing Values?
No
Variables Table
| Variable Name | Role | Type | Description | Units | Missing Values |
|---|---|---|---|---|---|
| no | |||||
| no | |||||
| no | |||||
| no | |||||
| no | |||||
| no | |||||
| no |
0 to 7 of 7
Additional Variable Information
6 molecular descriptors and 1 quantitative experimental response: 1) CIC0 2) SM1_Dz(Z) 3) GATS1i 4) NdsCH 5) NdssC 6) MLOGP 7) quantitative response, LC50 [-LOG(mol/L)]
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pip install ucimlrepo
from ucimlrepo import fetch_ucirepo # fetch dataset qsar_fish_toxicity = fetch_ucirepo(id=504) # data (as pandas dataframes) X = qsar_fish_toxicity.data.features y = qsar_fish_toxicity.data.targets # metadata print(qsar_fish_toxicity.metadata) # variable information print(qsar_fish_toxicity.variables)
Ballabio,Davide, Cassotti,Matteo, Consonni,Viviana, and Todeschini,Roberto. (2019). QSAR fish toxicity. UCI Machine Learning Repository. https://doi.org/10.24432/C5JG7B.
@misc{misc_qsar_fish_toxicity_504,
author = {Ballabio,Davide, Cassotti,Matteo, Consonni,Viviana, and Todeschini,Roberto},
title = {{QSAR fish toxicity}},
year = {2019},
howpublished = {UCI Machine Learning Repository},
note = {{DOI}: https://doi.org/10.24432/C5JG7B}
}Creators
Davide Ballabio
Matteo Cassotti
Viviana Consonni
Roberto Todeschini
DOI
License
This dataset is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.
This allows for the sharing and adaptation of the datasets for any purpose, provided that the appropriate credit is given.