Pavel Evdokimov1, Alexey Kudryavtsev2, Ekaterina Ilgisonis3, Elena Ponomarenko4, Andrey Lisitsa5. 1. Knowledge Technologies Ltd, Moscow, Russia. evdokp@gmail.com. 2. qB Ltd, Moscow, Russia. ookud@bk.ru. 3. Institute of Biomedical Chemistry, Moscow, Russia. ilgisonis.ev@gmail.com. 4. Institute of Biomedical Chemistry, Moscow, Russia. 2463731@gmail.com. 5. Institute of Biomedical Chemistry, Moscow, Russia. lisitsa063@gmail.com.
Abstract
BACKGROUND: Keeping up with journal articles on a daily basis is an important activity of scientists engaged in biomedical research. Usually, journal articles and papers in the field of biomedicine are accessed through the Medline/PubMed electronic library. In the process of navigating PubMed, researchers unknowingly generate user-specific reading profiles that can be shared within a social networking environment. This paper examines the structure of the social networking environment generated by PubMed users. METHODS: A web browser plugin was developed to map [in Medical Subject Headings (MeSH) terms] the reading patterns of individual PubMed users. RESULTS: We developed a scientific social network based on the personal research profiles of readers of biomedical articles. A browser plugin is used to record the digital object identifier or PubMed ID of web pages. Recorded items are posted on the activity feed and automatically mapped to PubMed abstract. Within the activity feed a user can trace back previously browsed articles and insert comments. By calculating the frequency with which specific MeSH occur, the research interests of PubMed users can be visually represented with a tag cloud. Finally, research profiles can be searched for matches between network users. CONCLUSIONS: A social networking environment was created using MeSH terms to map articles accessed through the Medline/PubMed online library system. In-network social communication is supported by the recommendation of articles and by matching users with similar scientific interests. The system is available at http://bioknol.org/en/.
BACKGROUND: Keeping up with journal articles on a daily basis is an important activity of scientists engaged in biomedical research. Usually, journal articles and papers in the field of biomedicine are accessed through the Medline/PubMed electronic library. In the process of navigating PubMed, researchers unknowingly generate user-specific reading profiles that can be shared within a social networking environment. This paper examines the structure of the social networking environment generated by PubMed users. METHODS: A web browser plugin was developed to map [in Medical Subject Headings (MeSH) terms] the reading patterns of individual PubMed users. RESULTS: We developed a scientific social network based on the personal research profiles of readers of biomedical articles. A browser plugin is used to record the digital object identifier or PubMed ID of web pages. Recorded items are posted on the activity feed and automatically mapped to PubMed abstract. Within the activity feed a user can trace back previously browsed articles and insert comments. By calculating the frequency with which specific MeSH occur, the research interests of PubMed users can be visually represented with a tag cloud. Finally, research profiles can be searched for matches between network users. CONCLUSIONS: A social networking environment was created using MeSH terms to map articles accessed through the Medline/PubMed online library system. In-network social communication is supported by the recommendation of articles and by matching users with similar scientific interests. The system is available at http://bioknol.org/en/.
Authors: Elena A Ponomarenko; Arthur T Kopylov; Andrey V Lisitsa; Sergey P Radko; Yana Yu Kiseleva; Leonid K Kurbatov; Konstantin G Ptitsyn; Olga V Tikhonova; Alexander A Moisa; Svetlana E Novikova; Ekaterina V Poverennaya; Ekaterina V Ilgisonis; Alexey D Filimonov; Nadezhda A Bogolubova; Valentina V Averchuk; Pavel A Karalkin; Igor V Vakhrushev; Konstantin N Yarygin; Sergei A Moshkovskii; Victor G Zgoda; Alexey S Sokolov; Alexander M Mazur; Egor B Prokhortchouck; Konstantin G Skryabin; Elena N Ilina; Elena S Kostrjukova; Dmitry G Alexeev; Alexander V Tyakht; Alexey Yu Gorbachev; Vadim M Govorun; Alexander I Archakov Journal: J Proteome Res Date: 2013-12-13 Impact factor: 4.466