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Official repository for the Topological Deep Learning Challenge 2024, organized by TAG-DS & PyT-Team and hosted by GRaM Workshop @ ICML 2024.

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Molecule Ring-Based Lifting (Graph to Cell)

Based on Jin et al. (2018), this implementation aims to condense a molecule ring into a single element. Utilizing the QM9 dataset, a benchmark dataset for molecule prediction, we develop a method to treat rings as 2-cell structures by identifying them through the provided SMILES representations of each molecule.

Here, the elements are the following:

  • Nodes: Atoms in the molecule.
  • Edges: Bonds between atoms.
  • 2-cells: Rings in the molecule.

Additionally, attributes inspired by those used in (Battiloro et al., 2024) are incorporated into the elements, enhancing the representation of the molecule. The attributes are:

  • Node: Atom type, atomic number, and chirality.
  • Edge: Bond type, conjugation and stereochemistry.
  • Rings: Ring size, aromaticity, heteroatoms, saturation, hydrophobicity, electrophilicity, nucleophilicity, and polarity.

This pull request is done under the team formed by: Bertran Miquel Oliver, Manel Gil Sorribes, Alexis Molina

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Official repository for the Topological Deep Learning Challenge 2024, organized by TAG-DS & PyT-Team and hosted by GRaM Workshop @ ICML 2024.

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