A structure-based, alignment-free embedding approach for proteins. Can be used as input to machine learning algorithms.

See the documentation.

Geometricus is a Python (3.9+) package with NumPy, SciPy, Numba, PyTorch and ProDy as dependencies.

Install with pip install git+https://github.com/TurtleTools/geometricus.git

See the Getting Started page for example usage.

Janani Durairaj, Mehmet Akdel, Dick de Ridder, Aalt D J van Dijk, Geometricus represents protein structures as shape-mers derived from moment invariants, Bioinformatics, Volume 36, Issue Supplement_2, December 2020, Pages i718–i725, https://doi.org/10.1093/bioinformatics/btaa839

Janani Durairaj, Mehmet Akdel, Dick de Ridder, Aalt D.J. van Dijk, Fast and adaptive protein structure representations for machine learning, bioRxiv 2021.04.07.438777; doi: https://doi.org/10.1101/2021.04.07.438777

Mehmet Akdel, Douglas E V Pires, Eduard Porta Pardo, Jürgen Jänes, Arthur O Zalevsky, Bálint Mészáros, Patrick Bryant, Lydia L. Good, Roman A Laskowski, Gabriele Pozzati, Aditi Shenoy, Wensi Zhu, Petras Kundrotas, Victoria Ruiz Serra, Carlos H M Rodrigues, Alistair S Dunham, David Burke, Neera Borkakoti, Sameer Velankar, Adam Frost, Kresten Lindorff-Larsen, Alfonso Valencia, Sergey Ovchinnikov, Janani Durairaj, David B Ascher, Janet M Thornton, Norman E Davey, Amelie Stein, Arne Elofsson, Tristan I Croll, Pedro Beltrao, A structural biology community assessment of AlphaFold 2 applications, bioRxiv 2021.09.26.461876; doi: https://doi.org/10.1101/2021.09.26.461876

Janani Durairaj, Joana Pereira, Mehmet Akdel, Torsten Schwede, What is hidden in the darkness? Characterization of AlphaFold structural space, bioRxiv 2022.10.11.511548; doi: https://doi.org/10.1101/2022.10.11.511548