MSIonization
MSIonization is a Python package for predicting the optimal ionization mode with higher ionization efficiency for organic molecules from their SMILES representations.
Features
1- Predict the optimal ionization mode (positive or negative) from SMILES using a Support Vector Machine (SVM) model.
2- Performs applicability domain analysis.
3- Displays prediction probabilities for both classes.
4- GUI support for easy use.
5- Multiprocessing support.
6- Error handling for invalid SMILES.
Built With
-Python: Recommended version is python ≥3.9.21.
-Fingerprint calculation: RDKit 2022.09.5
-Machine Learning: Scikit-learn 1.6.0
-Applicability Domain: Based on calculating leverage.
Link for more information:
1 maintainer
Metadata
1 maintainer
Release files for MSIonization 1.0.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| msionization-1.0.0-py3-none-any.whl | Python 3 | none | any | Details for msionization-1.0.0-py3-none-any.whl |
Release files / msionization-1.0.0-py3-none-any.whl
| Download URL | msionization-1.0.0-py3-none-any.whl |
|---|---|
| Size | 574.9 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
4f835ffe09f4f70e3a437f35d204741a77cc290b44349f9706364a40bb2ea74c
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.10.19
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Security for MSIonization 1.0.0
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