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Update Zenodo links
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CHANGELOG.md

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### 0.6.0 - TBD
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- Added new baseline methods
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- Added new baseline methods (AlphaFold 3, NeuralPLexer3, Chai-1 with multiple sequence alignments (MSAs))
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- Added new binding site-focused implementation of `complex_alignment.py` based on PyMOL's `align` command, which in many cases yields 3x better docking evaluation scores for baseline methods
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- Added new script for analyzing baseline methods' protein conformational changes w.r.t. input (e.g., AlphaFold) protein structures and the corresponding reference (crystal) protein structures
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- Added the new centroid RMSD and PLIF-EMD/WM metrics
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- Added a failure mode analysis notebook
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- Introducing DockGen-E, a new version of the DockGen benchmark dataset featuring enhanced biomolecular context for docking and co-folding predictions - namely, now all DockGen complexes represent the first (biologically relevant) bioassembly of the corresponding PDB structure
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- For the single-ligand datasets (i.e., Astex Diverse, PoseBusters Benchmark, and DockGen), now providing each baseline method with primary *and cofactor* ligand SMILES strings for prediction, to enhance the biomolecular context of these methods' predicted structures - as a result, for these single-ligand datasets, now the predicted ligand *most similar* to the primary ligand (in terms of both Tanimoto and structural similarity) is selected for scoring
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- Updated Chai-1's inference code to commit `44375d5d4ea44c0b5b7204519e63f40b063e4a7c`
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- Updated Chai-1's inference code to commit `44375d5d4ea44c0b5b7204519e63f40b063e4a7c`, and ran it also with NeuralPLexer3's (paired) MSAs
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- Replaced all AlphaFold 3 server predictions of each dataset's protein structures with predictions from AlphaFold 3's local inference code
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- With all the above changed in place, simplified, re-ran, and re-analyzed all baseline methods for each benchmark dataset, and updated the baseline predictions hosted on Zenodo
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- Pocket-only benchmarking has been deprecated
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- With all the above changed in place, simplified, re-ran, and re-analyzed all baseline methods for each benchmark dataset, and updated the baseline predictions and datasets (now containing standardized MSAs) hosted on Zenodo
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### 0.5.0 - 09/30/2024
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README.md

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# PoseBench
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[![Paper](http://img.shields.io/badge/arXiv-2405.14108-B31B1B.svg)](https://arxiv.org/abs/2405.14108)
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[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.13858866.svg)](https://doi.org/10.5281/zenodo.13858866)
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[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.14629652.svg)](https://doi.org/10.5281/zenodo.14629652)
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[![PyPI version](https://badge.fury.io/py/posebench.svg)](https://badge.fury.io/py/posebench)
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[![Project Status: Active – The project has reached a stable, usable state and is being actively developed.](https://www.repostatus.org/badges/latest/active.svg)](https://www.repostatus.org/#active)
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[![Docs](https://assets.readthedocs.org/static/projects/badges/passing-flat.svg)](https://bioinfomachinelearning.github.io/PoseBench/)
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```bash
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# fetch, extract, and clean-up preprocessed Astex Diverse, PoseBusters Benchmark, DockGen, and CASP15 data (~3 GB) #
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wget https://zenodo.org/records/13858866/files/astex_diverse_set.tar.gz
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wget https://zenodo.org/records/13858866/files/posebusters_benchmark_set.tar.gz
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wget https://zenodo.org/records/13858866/files/dockgen_set.tar.gz
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wget https://zenodo.org/records/13858866/files/casp15_set.tar.gz
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wget https://zenodo.org/records/14629652/files/astex_diverse_set.tar.gz
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wget https://zenodo.org/records/14629652/files/posebusters_benchmark_set.tar.gz
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wget https://zenodo.org/records/14629652/files/dockgen_set.tar.gz
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wget https://zenodo.org/records/14629652/files/casp15_set.tar.gz
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tar -xzf astex_diverse_set.tar.gz
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tar -xzf posebusters_benchmark_set.tar.gz
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tar -xzf dockgen_set.tar.gz
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```bash
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# fetch, extract, and clean-up benchmark method predictions to reproduce paper results (~19 GB) #
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# AutoDock Vina predictions and results
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wget https://zenodo.org/records/13858866/files/vina_benchmark_method_predictions.tar.gz
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wget https://zenodo.org/records/14629652/files/vina_benchmark_method_predictions.tar.gz
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tar -xzf vina_benchmark_method_predictions.tar.gz
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rm vina_benchmark_method_predictions.tar.gz
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# DiffDock predictions and results
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wget https://zenodo.org/records/13858866/files/diffdock_benchmark_method_predictions.tar.gz
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wget https://zenodo.org/records/14629652/files/diffdock_benchmark_method_predictions.tar.gz
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tar -xzf diffdock_benchmark_method_predictions.tar.gz
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rm diffdock_benchmark_method_predictions.tar.gz
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# DynamicBind predictions and results
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wget https://zenodo.org/records/13858866/files/dynamicbind_benchmark_method_predictions.tar.gz
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wget https://zenodo.org/records/14629652/files/dynamicbind_benchmark_method_predictions.tar.gz
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tar -xzf dynamicbind_benchmark_method_predictions.tar.gz
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rm dynamicbind_benchmark_method_predictions.tar.gz
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# RoseTTAFold-All-Atom predictions and results
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wget https://zenodo.org/records/13858866/files/rfaa_benchmark_method_predictions.tar.gz
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wget https://zenodo.org/records/14629652/files/rfaa_benchmark_method_predictions.tar.gz
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tar -xzf rfaa_benchmark_method_predictions.tar.gz
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rm rfaa_benchmark_method_predictions.tar.gz
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# Chai-1 predictions and results
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wget https://zenodo.org/records/13858866/files/chai_benchmark_method_predictions.tar.gz
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wget https://zenodo.org/records/14629652/files/chai_benchmark_method_predictions.tar.gz
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tar -xzf chai_benchmark_method_predictions.tar.gz
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rm chai_benchmark_method_predictions.tar.gz
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# AlphaFold 3 predictions and results
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wget https://zenodo.org/records/13858866/files/af3_benchmark_method_predictions.tar.gz
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wget https://zenodo.org/records/14629652/files/af3_benchmark_method_predictions.tar.gz
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tar -xzf af3_benchmark_method_predictions.tar.gz
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rm af3_benchmark_method_predictions.tar.gz
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# NeuralPLexer3 predictions and results
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wget https://zenodo.org/records/13858866/files/neuralplexer3_benchmark_method_predictions.tar.gz
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wget https://zenodo.org/records/14629652/files/neuralplexer3_benchmark_method_predictions.tar.gz
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tar -xzf neuralplexer3_benchmark_method_predictions.tar.gz
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rm neuralplexer3_benchmark_method_predictions.tar.gz
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```
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```bash
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# fetch, extract, and clean-up benchmark method interactions to reproduce paper results (~12 GB) #
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# cached ProLIF interactions for notebook plots
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wget https://zenodo.org/records/13858866/files/posebench_notebooks.tar.gz
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wget https://zenodo.org/records/14629652/files/posebench_notebooks.tar.gz
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tar -xzf posebench_notebooks.tar.gz
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rm posebench_notebooks.tar.gz
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```
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conda deactivate
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```
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**NOTE:** The preprocessed Astex Diverse, PoseBusters Benchmark, DockGen, and CASP15 data available via [Zenodo](https://doi.org/10.5281/zenodo.13858866) provide pre-holo-aligned protein structures predicted by AlphaFold 3 (and alternatively MIT-licensed ESMFold) for these respective datasets. Accordingly, users must ensure their usage of such predicted protein structures from AlphaFold 3 aligns with AlphaFold 3's [Terms of Use](https://github.com/google-deepmind/alphafold3/blob/main/WEIGHTS_TERMS_OF_USE.md).
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**NOTE:** The preprocessed Astex Diverse, PoseBusters Benchmark, DockGen, and CASP15 data available via [Zenodo](https://doi.org/10.5281/zenodo.14629652) provide pre-holo-aligned protein structures predicted by AlphaFold 3 (and alternatively MIT-licensed ESMFold) for these respective datasets. Accordingly, users must ensure their usage of such predicted protein structures from AlphaFold 3 aligns with AlphaFold 3's [Terms of Use](https://github.com/google-deepmind/alphafold3/blob/main/WEIGHTS_TERMS_OF_USE.md).
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</details>
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notebooks/astex_method_interaction_analysis_plotting.ipynb

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")\n",
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"assert os.path.exists(\n",
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" ad_set_dir\n",
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"), \"Please download the Astex Diverse set from `https://zenodo.org/records/13858866` before proceeding.\"\n",
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"), \"Please download the Astex Diverse set from `https://zenodo.org/records/14629652` before proceeding.\"\n",
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"\n",
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"# Mappings\n",
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"method_mapping = {\n",

notebooks/astex_method_interaction_analysis_plotting.py

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)
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assert os.path.exists(
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ad_set_dir
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), "Please download the Astex Diverse set from `https://zenodo.org/records/13858866` before proceeding."
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), "Please download the Astex Diverse set from `https://zenodo.org/records/14629652` before proceeding."
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# Mappings
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method_mapping = {

notebooks/casp15_method_interaction_analysis_plotting.ipynb

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")\n",
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"assert os.path.exists(\n",
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" casp15_set_dir\n",
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"), \"Please download the (public) CASP15 set from `https://zenodo.org/records/13858866` before proceeding.\"\n",
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"), \"Please download the (public) CASP15 set from `https://zenodo.org/records/14629652` before proceeding.\"\n",
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"\n",
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"# Mappings\n",
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"method_mapping = {\n",

notebooks/casp15_method_interaction_analysis_plotting.py

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)
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assert os.path.exists(
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), "Please download the (public) CASP15 set from `https://zenodo.org/records/13858866` before proceeding."
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), "Please download the (public) CASP15 set from `https://zenodo.org/records/14629652` before proceeding."
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# Mappings
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method_mapping = {

notebooks/dataset_interaction_analysis_plotting.ipynb

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")\n",
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"assert os.path.exists(\n",
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" ad_set_dir\n",
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"), \"Please download the Astex Diverse set from `https://zenodo.org/records/13858866` before proceeding.\"\n",
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"), \"Please download the Astex Diverse set from `https://zenodo.org/records/14629652` before proceeding.\"\n",
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"assert os.path.exists(\n",
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" pb_set_dir\n",
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"), \"Please download the PoseBusters Benchmark set from `https://zenodo.org/records/13858866` before proceeding.\"\n",
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"), \"Please download the PoseBusters Benchmark set from `https://zenodo.org/records/14629652` before proceeding.\"\n",
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"assert os.path.exists(\n",
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" dg_set_dir\n",
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"), \"Please download the DockGen set from `https://zenodo.org/records/13858866` before proceeding.\"\n",
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"), \"Please download the DockGen set from `https://zenodo.org/records/14629652` before proceeding.\"\n",
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"assert os.path.exists(\n",
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"), \"Please download the (public) CASP15 set from `https://zenodo.org/records/13858866` before proceeding.\"\n",
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"), \"Please download the (public) CASP15 set from `https://zenodo.org/records/14629652` before proceeding.\"\n",
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"\n",
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"CASP15_ANALYSIS_TARGETS_TO_SKIP = [\n",
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" \"T1170\"\n",

notebooks/dataset_interaction_analysis_plotting.py

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), "Please download the Astex Diverse set from `https://zenodo.org/records/13858866` before proceeding."
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), "Please download the Astex Diverse set from `https://zenodo.org/records/14629652` before proceeding."
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pb_set_dir
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), "Please download the PoseBusters Benchmark set from `https://zenodo.org/records/13858866` before proceeding."
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), "Please download the PoseBusters Benchmark set from `https://zenodo.org/records/14629652` before proceeding."
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), "Please download the DockGen set from `https://zenodo.org/records/14629652` before proceeding."
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), "Please download the (public) CASP15 set from `https://zenodo.org/records/13858866` before proceeding."
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), "Please download the (public) CASP15 set from `https://zenodo.org/records/14629652` before proceeding."
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notebooks/dockgen_method_interaction_analysis_plotting.ipynb

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")\n",
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"assert os.path.exists(\n",
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" dg_set_dir\n",
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"), \"Please download the DockGen set from `https://zenodo.org/records/13858866` before proceeding.\"\n",
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"), \"Please download the DockGen set from `https://zenodo.org/records/14629652` before proceeding.\"\n",
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"# Mappings\n",
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"method_mapping = {\n",

notebooks/dockgen_method_interaction_analysis_plotting.py

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), "Please download the DockGen set from `https://zenodo.org/records/14629652` before proceeding."
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# Mappings
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method_mapping = {

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