Physicochemical Properties of Protein Tertiary Structure
Donated on 3/30/2013
This is a data set of Physicochemical Properties of Protein Tertiary Structure. The data set is taken from CASP 5-9. There are 45730 decoys and size varying from 0 to 21 armstrong.
Dataset Characteristics
Multivariate
Subject Area
Biology
Associated Tasks
Regression
Feature Type
Real
# Instances
45730
# Features
-
Dataset Information
Has Missing Values?
No
Variables Table
| Variable Name | Role | Type | Description | Units | Missing Values |
|---|---|---|---|---|---|
| no | |||||
| no | |||||
| no | |||||
| no | |||||
| no | |||||
| no | |||||
| no | |||||
| no | |||||
| no |
0 to 9 of 9
Additional Variable Information
RMSD-Size of the residue. F1 - Total surface area. F2 - Non polar exposed area. F3 - Fractional area of exposed non polar residue. F4 - Fractional area of exposed non polar part of residue. F5 - Molecular mass weighted exposed area. F6 - Average deviation from standard exposed area of residue. F7 - Euclidian distance. F8 - Secondary structure penalty. F9 - Spacial Distribution constraints (N,K Value).
Dataset Files
| File | Size |
|---|---|
| CASP.csv | 3.4 MB |
Reviews
There are no reviews for this dataset yet.
pip install ucimlrepo
from ucimlrepo import fetch_ucirepo # fetch dataset physicochemical_properties_of_protein_tertiary_structure = fetch_ucirepo(id=265) # data (as pandas dataframes) X = physicochemical_properties_of_protein_tertiary_structure.data.features y = physicochemical_properties_of_protein_tertiary_structure.data.targets # metadata print(physicochemical_properties_of_protein_tertiary_structure.metadata) # variable information print(physicochemical_properties_of_protein_tertiary_structure.variables)
Rana, P. (2013). Physicochemical Properties of Protein Tertiary Structure [Dataset]. UCI Machine Learning Repository. https://doi.org/10.24432/C5QW3H.
Creators
Prashant Rana
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.