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A simple tool to predict the general toxicity and calculate the synthesize accessibility (SA) score for small molecules.

License: GNU General Public License v3.0

Python 100.00%
toxicity-prediction sascore-prediction

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etoxpred's Issues

About theano

Is it must to use theano? Because theano will not get support anymore, so people use tensorflow instead, especially for keras users. I read your code. You used theano for graph. Do you have alternatives? Many thanks.

Trained Model

I want to use the trained model and predict the toxicity of new molecules. How can I use your tool? Can you please explain? Should I go about using the joblib or py file? How do I give input files in the model to test? readme is not much clear. Kindly elaborate.

Documentation

Could you maybe provide a documentation on how to include your library into a self written program? That would help alot. :-)

Datasets Availability

Can you provide datasets for specific toxicities. They are not available in the dataset link mentioned in paper.

{Critical} Value Error: node array from pickle has incompatible dtype

Hello, Thanks for this wonderful repo!

When i git clone and run this using python etoxpred_predict.py --datafile tcm600_nr.smi --modelfile etoxpred_best_model.joblib --outputfile results.csv (after unzippiing tar) i get this error:

...loading models
C:\Users\Sri Raghu\AppData\Local\Programs\Python\Python312\Lib\site-packages\sklearn\base.py:376: InconsistentVersionWarning: Trying to unpickle estimator ExtraTreeClassifier from version 0.23.2 when using version 1.4.0. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:
https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations
  warnings.warn(
Traceback (most recent call last):
  File "C:\Users\Sri Raghu\Desktop\swift-trials\ind-projects\eToxPred\etoxpred_predict.py", line 74, in <module>
    predict(opt)
  File "C:\Users\Sri Raghu\Desktop\swift-trials\ind-projects\eToxPred\etoxpred_predict.py", line 59, in predict
    clf = load(opt.modelfile)
          ^^^^^^^^^^^^^^^^^^^
  File "C:\Users\Sri Raghu\AppData\Local\Programs\Python\Python312\Lib\site-packages\joblib\numpy_pickle.py", line 658, in load
    obj = _unpickle(fobj, filename, mmap_mode)
          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\Sri Raghu\AppData\Local\Programs\Python\Python312\Lib\site-packages\joblib\numpy_pickle.py", line 577, in _unpickle
    obj = unpickler.load()
          ^^^^^^^^^^^^^^^^
  File "C:\Users\Sri Raghu\AppData\Local\Programs\Python\Python312\Lib\pickle.py", line 1205, in load
PS C:\Users\Sri Raghu\Desktop\swift-trials\ind-projects\eToxPred> python etoxpred_predict.py --datafile tcm600_nr.smi --modelfile etoxpred_best_model.joblib --outputfile results.csv
...loading models
C:\Users\Sri Raghu\AppData\Local\Programs\Python\Python312\Lib\site-packages\sklearn\base.py:376: InconsistentVersionWarning: Trying to unpickle estimator ExtraTreeClassifier from version 0.23.2 when using version 1.4.0. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:
https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations
  warnings.warn(
Traceback (most recent call last):
  File "C:\Users\Sri Raghu\Desktop\swift-trials\ind-projects\eToxPred\etoxpred_predict.py", line 74, in <module>
    predict(opt)
  File "C:\Users\Sri Raghu\Desktop\swift-trials\ind-projects\eToxPred\etoxpred_predict.py", line 59, in predict
    clf = load(opt.modelfile)
          ^^^^^^^^^^^^^^^^^^^
  File "C:\Users\Sri Raghu\AppData\Local\Programs\Python\Python312\Lib\site-packages\joblib\numpy_pickle.py", line 658, in load
    obj = _unpickle(fobj, filename, mmap_mode)
          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\Sri Raghu\AppData\Local\Programs\Python\Python312\Lib\site-packages\joblib\numpy_pickle.py", line 577, in _unpickle
    obj = unpickler.load()
          ^^^^^^^^^^^^^^^^
  File "C:\Users\Sri Raghu\AppData\Local\Programs\Python\Python312\Lib\pickle.py", line 1205, in load
    dispatch[key[0]](self)
  File "C:\Users\Sri Raghu\AppData\Local\Programs\Python\Python312\Lib\site-packages\joblib\numpy_pickle.py", line 402, in load_build
    Unpickler.load_build(self)
  File "C:\Users\Sri Raghu\AppData\Local\Programs\Python\Python312\Lib\pickle.py", line 1710, in load_build
    setstate(state)
  File "sklearn\\tree\\_tree.pyx", line 865, in sklearn.tree._tree.Tree.__setstate__
  File "sklearn\\tree\\_tree.pyx", line 1571, in sklearn.tree._tree._check_node_ndarray
ValueError: node array from the pickle has an incompatible dtype:
- expected: {'names': ['left_child', 'right_child', 'feature', 'threshold', 'impurity', 'n_node_samples', 'weighted_n_node_samples', 'missing_go_to_left'], 'formats': ['<i8', '<i8', '<i8', '<f8', '<f8', '<i8', '<f8', 'u1'], 'offsets': [0, 8, 16, 24, 32, 40, 48, 56], 'itemsize': 64}
- got     : [('left_child', '<i8'), ('right_child', '<i8'), ('feature', '<i8'), ('threshold', '<f8'), ('impurity', '<f8'), ('n_node_samples', '<i8'), ('weighted_n_node_samples', '<f8')]

I tired reducing sk-learn to base version -> didnt work
installed MS visual tools and C++ tools -> didnt work

Kindly help me through this. Much Appreciated

Installation Issues

I'm facing some issues with installing this software, more precisely clashes in the versions of the different libraries used (despite using conda, a well-known package management system).

Can we please get more details on the development environment in which the software was created?
Ideally, a requirements.txt or Dockerfile file.

Thanks.

64 bit sklearn decision tree on 32 bit python

Hello,

I recently downloaded all dependencies (as you have listed) to all same versions other than openbabel 2.3.2 instead of 2.3.1. When I run the code, I get the following error...
Traceback (most recent call last): File "etoxpred.py", line 121, in <module> predicted_values,proba = predict(X,'SA_trained_model_cpu.pkl','Tox_trained_model.pkl') # if cuda is not installed, use the trained_model_cpu File "etoxpred.py", line 113, in predict xtree = joblib.load(tox_model) File "C:\Python27\lib\site-packages\sklearn\externals\joblib\numpy_pickle.py", line 575, in load obj = _unpickle(fobj, filename, mmap_mode) File "C:\Python27\lib\site-packages\sklearn\externals\joblib\numpy_pickle.py", line 507, in _unpickle obj = unpickler.load() File "C:\Python27\lib\pickle.py", line 864, in load dispatch[key](self) File "C:\Python27\lib\pickle.py", line 1139, in load_reduce value = func(*args) File "sklearn\tree\_tree.pyx", line 584, in sklearn.tree._tree.Tree.__cinit__ (sklearn\tree\_tree.c:7533) ValueError: Buffer dtype mismatch, expected 'SIZE_t' but got 'long long'

Which the internet says is from the mismatched bit versions. I could download a 64 bit python, but openbabel only works on 32 bit python. Let me know if you get any issues when trying to run it

Extracting necessary files to use prediction in Jupityr Notebook.

Hello, I am a little new to python and was wondering if there was a more detailed description on how to extract the necessary files for this package to work.

I downloaded the entire package (.py, .smi, and .pkl files) but am struggling to get the predictor started.

  1. What is the best way to extract the package through the Jupityr environment?
  2. I have tried to copy and paste the necessary code into a single notebook, but get errors each time. Running python etoxpred_predict.py --datafile tcm600_nr.smi --modelfile etoxpred_best_model.joblib --outputfile results.csv gives me an invalid syntax error. Should I be changing anything in this line of code?

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