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Systematic Analysis of Endometrial Cancer-Associated Hub Proteins Based on Text Mining
Joint Authors
Source
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-6, 6 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-08-23
Country of Publication
Egypt
No. of Pages
6
Main Subjects
Abstract EN
Objective.
The aim of this study was to systematically characterize the expression of endometrial cancer- (EC-) associated genes and to analysis the functions, pathways, and networks of EC-associated hub proteins.
Methods.
Gene data for EC were extracted from the PubMed (MEDLINE) database using text mining based on NLP.
PPI networks and pathways were integrated and obtained from the KEGG and other databases.
Proteins that interacted with at least 10 other proteins were identified as the hub proteins of the EC-related genes network.
Results.
A total of 489 genes were identified as EC-related with P < 0.05 , and 32 pathways were identified as significant ( P < 0.05 , F D R < 0.05 ).
A network of EC-related proteins that included 271 interactions was constructed.
The 17 proteins that interact with 10 or more other proteins ( P < 0.05 , F D R < 0.05 ) were identified as the hub proteins of this PPI network of EC-related genes.
These 17 proteins are EGFR, MET, PDGFRB, CCND1, JUN, FGFR2, MYC, PIK3CA, PIK3R1, PIK3R2, KRAS, MAPK3, CTNNB1, RELA, JAK2, AKT1, and AKT2.
Conclusion.
Our data may help to reveal the molecular mechanisms of EC development and provide implications for targeted therapy for EC.
However, corrections between certain proteins and EC continue to require additional exploration.
American Psychological Association (APA)
Gao, Huiqiao& Zhang, Zhenyu. 2015. Systematic Analysis of Endometrial Cancer-Associated Hub Proteins Based on Text Mining. BioMed Research International،Vol. 2015, no. 2015, pp.1-6.
https://search.emarefa.net/detail/BIM-1056135
Modern Language Association (MLA)
Gao, Huiqiao& Zhang, Zhenyu. Systematic Analysis of Endometrial Cancer-Associated Hub Proteins Based on Text Mining. BioMed Research International No. 2015 (2015), pp.1-6.
https://search.emarefa.net/detail/BIM-1056135
American Medical Association (AMA)
Gao, Huiqiao& Zhang, Zhenyu. Systematic Analysis of Endometrial Cancer-Associated Hub Proteins Based on Text Mining. BioMed Research International. 2015. Vol. 2015, no. 2015, pp.1-6.
https://search.emarefa.net/detail/BIM-1056135
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1056135