Open AccessTowards Automated Meta-analysis of Biomedical Texts in the Field of Cell-based Immunotherapy
Author(s) -
Dmitry Devyatkin,
А.И. Молодченков,
Ajvor Lukin,
Y.S. Kim,
Anna A. Boyko,
П. А. Каралкин,
Jui-Chin Chiang,
Galina Volkova,
A. Yu. Lupatov
Publication year - 2019
Publication title -
biomedical chemistry: research and methods
Language(s) - English
Resource type - Journals
ISSN - 2618-7531
DOI - 10.18097/bmcrm00109
Subject(s) - immunotherapy , immune system , cancer immunotherapy , medicine , computational biology , cell , computer science , immunology , biology , genetics
Cell-based immunotherapy is a promising approach for the treatment of chronic infections, autoimmune disorders, and malignant tumors. There are many strategies of cell-based immunotherapy of cancer; these include injection of various immune effector cells, propagated and «trained» in a cell culture. Alternatively, cells presenting tumor antigens on their surface in a form recognized by the immune system can be used to achieve a therapeutic effect. The research results in this field are presented in thousands of texts, and their manual analysis is very complicated. We have developed an approach for automated text analysis in this area of biomedical science. Here we present the first results of the automated analysis of the data extracted from abstracts of scientific articles available in PubMed. These results demonstrate the associations between types of tumors and the most commonly used methods of their cell-based immunotherapy.