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Tool for mining structure-property relationships from chemical datasets
This project forked from drrdom/spci
Tool for mining structure-property relationships from chemical datasets
SPCI ----- Tool for mining structure-property relationships from chemical datasets Description ----- Retrieves structure-property relationship from datasets in a chemically meaningful way. Returns estimated contributions of fragments to the investigated property of compounds from a data set and can estimate contribution of different physicochemical factors as well. Features ----- 1. Easy to use straightforward workflow with GUI. 2. Automatic model building and cross-validation. 3. Build models for imbalanced data set using the multiple oversampling approach. 4. Prediction with built models. 5. Several fragmentation schemes to compute fragment contributions of: a) ring systems; b) Murcko scaffolds; c) common functional groups and rings; d) user-defined fragments; e) automatically generated fragments (based on SMARTS pattern matched broken bonds). Visualization of results ----- 1. Built-in visualization. 2. rspci - R package for custom visualization (https://github.com/DrrDom/rspci) 3. Online tool for visualization, plot customization and figure downloading (link will be published soon) Manual ----- Short manual is included. Publications ----- Structural interpretation was published in the paper http://dx.doi.org/10.1002/minf.201300029 Integrated structural and physicochemical interpretation was published in the paper http://dx.doi.org/10.1021/acs.jcim.6b00371 Citation ----- If you use this tool please cite this repository and the publication J. Chem. Inf. Model. 56, 8, 1455-1469 (http://dx.doi.org/10.1021/acs.jcim.6b00371) Home page ----- http://qsar4u.com/pages/sirms_qsar.php License ----- GPLv3 What's new ----- **1.0.0** - RDKit is used as a backend instead of Indigo - multiple undersampling was implemented - changed default descriptors, that make this version incompatible with previous models and vice versa. - updated sirms descriptors - many small fixes and improvements
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