Dataset for: Revisiting Molecular Descriptors with TDiMS for Interpretable Intramolecular Interactions Based on Substructure Pairs

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Authors: Lisa Hamada, Akihiro Kishimoto, Kohei Miyaguchi, Masataka Hirose, Junta Fuchiwaki, Indra Priyadarsini, Seiji Takeda
Cited by: 1

Abstract

This record contains the minimum datasets required to interpret, verify and extend the findings reported in the associated manuscript, “Revisiting Molecular Descriptors with TDiMS for Interpretable Intramolecular Interactions Based on Substructure Pairs”. The deposited files include the exact subsets used in the Chromophore, QM9 and PubChemQC analyses, including HAC-binned PubChemQC subsets used in supplementary analyses. The record also includes documentation describing file contents, provenance and reuse conditions. Source data for figures are provided with the paper and are not included in this Zenodo record.

Fields of Study & Subjects

Computational Drug Discovery Methods Machine Learning in Materials Science Molecular spectroscopy and chirality

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
1 January 2026
Language
EN