Construction of protein semantic networks using PubMed/MEDLINE
作者： E. A. Ponomarenko , A. V. Lisitsa , E. V. Il’gisonis , A. I. Archakov
DOI: 10.1134/S0026893310010176
关键词: Construct (python library) 、 Human proteins 、 Base sequence 、 MEDLINE 、 Bioinformatics 、 Context (language use) 、 Natural language processing 、 Artificial intelligence 、 Edge density 、 Computer science 、 Semantic network
摘要: A method for constructing protein semantic networks using MEDLINE abstracts is proposed. The publications retrieved by the context search names (relevant) and related were used. proposed based on estimation of connectivity between proteins. score was calculated as a function number relevant or papers found pair This used to construct network 150 human proteins belonging five different metabolic pathways. Analysis demonstrated that involved in associated molecular processes formed subgraphs with high edge density.
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sci-hub.se 参考文章(15)
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