ArticleScientific reports2018
Linguistic measures of chemical diversity and the "keywords" of molecular collections.
Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Navigating chemical-linguistic sharing space with heterogeneous molecular encoding.Nature communications · 2026Article
- GraphTransDTA: Drug-Target Affinity Prediction with Graph Transformer for Multimodal Data Fusion.Interdisciplinary sciences, computational life sciences · 2026Article
- Drug-target binding affinity prediction based on power graph and word2vec.BMC medical genomics · 2025Article
- Article
- LSTM-SAGDTA: Predicting Drug-target Binding Affinity with an Attention Graph Neural Network and LSTM Approach.Current pharmaceutical design · 2024Article
- Article
- SSGraphCPI: A Novel Model for Predicting Compound-Protein Interactions Based on Deep Learning.International journal of molecular sciences · 2022Article
- Solubility Prediction from Molecular Properties and Analytical Data Using an In-phase Deep Neural Network (Ip-DNN).ACS omega · 2021Article
- Deep Learning in Virtual Screening: Recent Applications and Developments.International journal of molecular sciences · 2021Review
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Computerized linguistic analyses have proven of immense value in comparing and searching through large text collections ("corpora"), including those deposited on the Internet - indeed, it would nowadays be hard to imagine browsing the Web without, for instance, search algorithms extracting most appropriate keywords from documents. This paper describes how such corpus-linguistic concepts can be extended to chemistry based on characteristic "chemical words" that span more than traditional functional groups and, instead, look at common structural fragments molecules share. Using these words, it is possible to quantify the diversity of chemical collections/databases in new ways and to define molecular "keywords" by which such collections are best characterized and annotated.
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Registered trials
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