Alphapulldown

New features added:
1. Refactorised the codes; introduced folding_backend 303 thanks for the help from maurerv and DimaMolod
2. Allow the user to pad input matrices to desired number of MSAs and desired number of residues to speed up overall modelling process and avoid unnecessary re-compiling of AlphaFold neural network.
3. New way of modelling with customised structure templates without the need of recalculating the features again. 268
4. Separated post-modelling processes from prediction process 297 by DimaMolod
5. Supports full mmseqs2 mode i.e. without the need of local structural template database when using mmseqs mode 233

Bugs fixed:
1. Fixed incorrect colour scheme when ploting structures in jupyter-notebook 304 thanks for the help from gchojnowski and report from gilep
2. Fixed operands broadcast error when the features are created by mmseqs2 287 thanks for the report from Qrouger
3. Updated alpha-analysis.sif to avoid crashes when no model satisfies the cutoff value 307
4. Fix the config.cfg to avoid installing tensorflow versions that are not compatible with GPUs without latest CUDA. 298 Thanks for the help from kashyapchhatbar

Notice:
Apart from installing the beta version of alphapulldown from pypi, using pip install alphapulldown==2.0.0b1, please re-download the alpha-analysis singularity images again.
If your results are from AlphaPulldown prior to version 1.0.0, please use the link: [`alpha-analysis_jax_0.3.sif`](https://www.embl-hamburg.de/AlphaPulldown/downloads/alpha-analysis_jax_0.3.sif).
If your results are from AlphaPulldown with version >=1.0.0, please use the link: [`alpha-analysis_jax_0.4.sif`](https://www.embl-hamburg.de/AlphaPulldown/downloads/alpha-analysis_jax_0.4.sif).

Bugs fixed:

1. Fixed the incorrectly installed alphafold submodule 232 many thanks for the help from aokosinska
2. Fixed the import issue from biopython 234 and 231 Thanks for the help from aokosinska and grandrea
3. Fixed the create_notebook.py issue 211

Bugs fixed:

1. Fixed the incorrectly installed AlphaLink2 submodule 224
2. removed jax dependency when saving results pickles. credits to DimaMolod 06461b8

- Fix feature generation with mmseqs2 and the new ColabFold API. Added tokens, print ColabFold citation when --mmseqs2=True.
- Fix a bug when removing clashes and low plddt residues from the template.
- Added corresponding tests.
- Don't import run_alphafold if already imported (credits to gchojnowski)

- Fix for generating features with multimeric mmCIF templates. Correctly map sequence from entity_poly_seq table with Biopython structure when auth_seq_id is different from label_seq_id in atom_site table.

What's Changed
* Update Python version and jax version. Please be aware that the singularity image was updated as well. There are now 2 singularity images, one for the results generated by AlphaPulldown prior than version 1.0.0 and the other for the predictions generated by AlphaPulldown after version 1.0.0. Please check the details in Section 3 in [example_1.md](https://github.com/KosinskiLab/AlphaPulldown/blob/main/manuals/example_1.md) or [example_2.md](https://github.com/KosinskiLab/AlphaPulldown/blob/main/manuals/example_2.md)
* Allow the users to integrate cross-link mass spec data with AlphaFold predictions via AlphaLink2. Please refer to [run_with_AlphaLink2.md](https://github.com/KosinskiLab/AlphaPulldown/blob/main/manuals/run_with_AlphaLink2.md) for the details.

* Can use multimeric templates for guiding AlphaFold predictions, please refer to [example_3.md](https://github.com/KosinskiLab/AlphaPulldown/blob/main/manuals/example_3.md) for details. Credits to DimaMolod
* Added options to compress or remove pickle files in the results directories so that the output directories take much smaller space. Thanks to the advice from joshtburdick