A Retrieval System of Medicine Molecules Based on Graph Similarity

Qu, Jingwei; Sun, Penghui; Li, Xin; Wang, Bei; Lu, Xiaofeng; Tang, Zhi; Zhang, Chengcui

doi:10.1109/mmul.2019.2902092

Cited by 3 publications

(1 citation statement)

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“…Text-based retrieval includes tasks such as finding relevant papers for a chemical or reaction and chemical entity recognition. Much work has also been done in graph and molecule-based retrieval (Hagadone, 1992;Barnard, 1993;Yan et al, 2005;Kratochvíl et al, 2018;Qu et al, 2019;Kratochvíl, 2019;Goyal et al, 2020). Hybrid approaches have also been attempted; Zhou et al (2010) replace chemical entities in text with a unique canonical key (thus standardizing synonyms).…”

Section: Substructure or Description Retrievalmentioning

confidence: 99%

Text2Mol: Cross-Modal Molecule Retrieval with Natural Language Queries

Edwards¹,

Zhai²,

Ji³

2021

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing

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We propose a new task, Text2Mol, to retrieve molecules using natural language descriptions as queries. Natural language and molecules encode information in very different ways, which leads to the exciting but challenging problem of integrating these two very different modalities. Although some work has been done on text-based retrieval and structurebased retrieval, this new task requires integrating molecules and natural language more directly. Moreover, this can be viewed as an especially challenging cross-lingual retrieval problem by considering the molecules as a language with a very unique grammar. We construct a paired dataset of molecules and their corresponding text descriptions, which we use to learn an aligned common semantic embedding space for retrieval. We extend this to create a cross-modal attention-based model for explainability and reranking by interpreting the attentions as association rules. We also employ an ensemble approach to integrate our different architectures, which significantly improves results from 0.372 to 0.499 MRR. This new multimodal approach opens a new perspective on solving problems in chemistry literature understanding and molecular machine learning. 1 1 The programs and data are publicly available at github.com/cnedwards/text2mol for research purposes.Water is an oxygen hydride consisting of an oxygen atom that is covalently bonded to two hydrogen atoms.

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