https://github.com/unixjunkie/tox21baseline
mirror of https://spotlite.nih.gov/opensource/tox21baseline.git
https://github.com/unixjunkie/tox21baseline
Last synced: 9 months ago
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mirror of https://spotlite.nih.gov/opensource/tox21baseline.git
- Host: GitHub
- URL: https://github.com/unixjunkie/tox21baseline
- Owner: UnixJunkie
- Created: 2019-06-13T07:12:03.000Z (about 7 years ago)
- Default Branch: master
- Last Pushed: 2019-06-13T08:07:52.000Z (about 7 years ago)
- Last Synced: 2025-09-05T11:40:43.641Z (10 months ago)
- Language: Java
- Homepage: https://spotlite.nih.gov/opensource/tox21baseline
- Size: 18.3 MB
- Stars: 1
- Watchers: 0
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
The Tox21 Challenge baseline models
===================================
This repository contains a simple implementation of the [naive
Bayes](http://en.wikipedia.org/wiki/Naive_Bayes_classifier) classifier
to provide baseline models for the 12 datasets in the [Tox21
Challenge](https://tripod.nih.gov/tox21/challenge). The
implementation makes use of [LyChI](https://github.com/ncats/lychi)
for structure standardization and
[PCFP](https://bitbucket.org/caodac/pcfp) for descriptor/feature
extraction. Please note that this code is for demonstration
purposes only; we make no claims as to its validity or correctness. We
do, however, encourage you to apply the models as-is (see below for
instructions) and submit the results to get a feel for what to
expect.
Compiling the code
==================
The code is self-contained in that all you need is a recent version of
the [Java](http://www.oracle.com/technetwork/java/) development kit (e.g.,
JDK 6+) and [Apache ant](http://ant.apache.org). To compile the code,
simply type ```ant``` at the command line. This step is optional as
the code is automatically compiled when any of the commands below is
invoked.
Training the classifier
=======================
The code comes bundled with prebuilt models under the ```models```
directory. However, if you want to build new set of models based on
tweaks you've made to the code, simply type the following on the
command line:
```
ant train
```
If all goes well, this command will generate the following 12 files,
one for each respective model.
```
NR-AHR.props
NR-AR-LBD.props
NR-AR.props
NR-AROMATASE.props
NR-ER-LBD.props
NR-ER.props
NR-PPAR-GAMMA.props
SR-ARE.props
SR-ATAD5.props
SR-HSE.props
SR-MMP.props
SR-P53.props
```
To test these models, simply move them to the ```models``` directory
(thereby replacing the old ones) and type ```ant predict``` (see
below) to test out the new models.
Generating predictions
======================
To apply the models to test dataset, simply run the following command:
```
ant predict
```
Upon successful execution, the following files are generated:
```
NR-AHR.txt
NR-AR-LBD.txt
NR-AR.txt
NR-AROMATASE.txt
NR-ER-LBD.txt
NR-ER.txt
NR-PPAR-GAMMA.txt
SR-ARE.txt
SR-ATAD5.txt
SR-HSE.txt
SR-MMP.txt
SR-P53.txt
```
Each file is in the proper format for [submission]
(https://tripod.nih.gov/tox21/challenge/submissions.jsp).
Contact
=======
For questions and/or problems with the code, please feel free to
contact the Tox21 team at . Good
luck with the competition!