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Automatic Recognition of Chemical Entity Mentions in Texts of Scientific Publications

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Automatic Documentation and Mathematical Linguistics Aims and scope

Abstract—

The huge space of experimental data on biological and chemical objects and their interactions contributes to the rapid growth of scientific publications containing their analysis. Such data may include characteristics of low-molecular-weight compounds, results of their biological activity evaluation, and their interaction with human and animal proteins, methods of synthesis of organic compounds, and their classification. The past decades saw the development of methods for automated extraction of data from texts of scientific publications, including those for retrieval of names of organic compounds. These data can be used for the automatic identification of the names of organic compounds, including all possible synonyms. Since the topics of scientific publications are diverse, the extracted data can be applied to obtain information about (1) classification of organic compounds (2) methods of synthesis of a given organic compound; (3) physicochemical properties of this compound; (4) its interaction with high-molecular-weight compounds (including proteins, mRNA of animals and humans); and (5) the therapeutic properties of organic compounds, the active substance of the drug, and data on clinical trials. This review considers the methods aimed at searching and extracting data on names of low-molecular-weight compounds and interactions between them and animal and human proteins (biological objects), as well as data on experimentally confirmed biological activity and the effects of organic compounds (including drugs) on pathological processes. Here, we discuss the methods developed and the results of their application published over the past 10 years.

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Funding

The study was financed by the Russian Science Foundation (project no. 19-15-00396).

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Authors and Affiliations

  1. Orekhovich Research Institute of Biomedical Chemistry, 119435, Moscow, Russia

    N. Yu. Biziukova, O. A. Tarasova, A. V. Rudik, D. A. Filimonov & V. V. Poroikov

  2. Pirogov Russian National Research Medical University, 117997, Moscow, Russia

    N. Yu. Biziukova

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  1. N. Yu. Biziukova
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  2. O. A. Tarasova
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  3. A. V. Rudik
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  4. D. A. Filimonov
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Correspondence to N. Yu. Biziukova, O. A. Tarasova, A. V. Rudik, D. A. Filimonov or V. V. Poroikov.

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Biziukova, N.Y., Tarasova, O.A., Rudik, A.V. et al. Automatic Recognition of Chemical Entity Mentions in Texts of Scientific Publications. Autom. Doc. Math. Linguist. 54, 306–315 (2020). https://doi.org/10.3103/S0005105520060023

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