NOTICE

NOCTURNAL - Third Party Notices and Attributions

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Chemical Space Visualization Components
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Portions of the chemical space visualization functionality in this project are
derived from work by Vincent F. Scalfani (original project: CSN_tutorial)(https://github.com/vfscalfani/CSN_tutorial/tree/main) 
Licensed under BSD 3-Clause License

Original Copyright Notice:
Copyright (c) 2022, Vincent F. Scalfani
All rights reserved.

Key Modifications Made:
- Integrated with NOCTURNAL's ML training pipelines and drug optimization algorithm "MutaGen" -> specialized to output chemical space network graphs for the optimized and optima compounds that are produced with MutaGen
- Modularized codeblocks into classes and function toolsets to:
	a) generate calculated data (Tanimoto similarity, MCS)
	b) visualize the chemical space network
- added 3 intelligent node sampling modes to prevent performance bottlenecks in pairwise similarity calculations
- pIC50 determines highlight colour instead of pKi
- Edge weight for constructing the CSN graph can be changed between Tanimoto similarity, MCS, or a hybrid method combining both, where the bias towards one can be set in the config file -> 'tanimoto_bias' (default = 0.5)
- Replaced matplotlib with Plotly for interactive visualization
- Implemented adaptive 2D molecular image sizing
- Adaptive network density to subset size
- Graph cosmetic customizability from config file
- Interactive nodes with hover text displaying: SMILES, pIC50 % rank, pIC50
- Various error handling blocks 


The original BSD 3-Clause License is included below:

BSD 3-Clause License

Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:

1. Redistributions of source code must retain the above copyright notice, this
   list of conditions and the following disclaimer.

2. Redistributions in binary form must reproduce the above copyright notice,
   this list of conditions and the following disclaimer in the documentation
   and/or other materials provided with the distribution.

3. Neither the name of the copyright holder nor the names of its
   contributors may be used to endorse or promote products derived from
   this software without specific prior written permission.

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