Surface Molecular Markers of Cancer Stem Cells: Computation Analysis of Full-Text Scientific Articles


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详细

The data on cancer stem cell surface molecular markers of 27 most common cancer diseases were analyzed using natural language processing and data mining techniques. As a source, 8933 full-text open-access English-language scientific articles available on the Internet were used. Text mining was based on searching for three entities within one sentence, namely a tumor name, a phrase “cancer stem cells” or its synonym, and a name of differentiation cluster molecule. As a result, a list of surface molecular markers was formed that included markers most frequently mentioned in the context of certain tumor diseases and used in studies of human and animal tumor cells. Based on similarity of the associated markers, the tumors were divided into five groups.

作者简介

R. Suvorov

Federal Research Center Computer Science and Control, Russian Academy of Sciences

Email: alupatov@mail.ru
俄罗斯联邦, Moscow

Ya. Kim

V. N. Orekhovich Research Institute of Biomedical Chemistry

Email: alupatov@mail.ru
俄罗斯联邦, Moscow

A. Gisina

V. N. Orekhovich Research Institute of Biomedical Chemistry

Email: alupatov@mail.ru
俄罗斯联邦, Moscow

J. Chiang

National Cheng Kung University

Email: alupatov@mail.ru
台湾, Tainan City

K. Yarygin

V. N. Orekhovich Research Institute of Biomedical Chemistry

Email: alupatov@mail.ru
俄罗斯联邦, Moscow

A. Lupatov

V. N. Orekhovich Research Institute of Biomedical Chemistry

编辑信件的主要联系方式.
Email: alupatov@mail.ru
俄罗斯联邦, Moscow


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