scholarly journals A Tree Kernel-Based Method for Protein-Protein Interaction Mining from Biomedical Literature

2006 ◽  
pp. 42-52 ◽  
Author(s):  
Jae-Hong Eom ◽  
Sun Kim ◽  
Seong-Hwan Kim ◽  
Byoung-Tak Zhang
Keyword(s):  
Protein Interaction ◽  
Biomedical Literature ◽  
Protein Protein Interaction ◽  
Tree Kernel

scholarly journals Distributed smoothed tree kernel for protein-protein interaction extraction from the biomedical literature

PLoS ONE ◽  
2017 ◽  
Vol 12 (11) ◽  
pp. e0187379 ◽  
Author(s):  
Gurusamy Murugesan ◽  
Sabenabanu Abdulkadhar ◽  
Jeyakumar Natarajan
Keyword(s):  
Protein Interaction ◽  
Biomedical Literature ◽  
Protein Protein Interaction ◽  
Tree Kernel ◽  
Interaction Extraction

scholarly journals HMNPPID—human malignant neoplasm protein–protein interaction database

2019 ◽  
Vol 13 (S1) ◽  
Author(s):  
Qingqing Li ◽  
Zhihao Yang ◽  
Zhehuan Zhao ◽  
Ling Luo ◽  
Zhiheng Li ◽  
...  
Keyword(s):  
Protein Interaction ◽  
Protein Interactions ◽  
Molecular Mechanisms ◽  
Malignant Neoplasm ◽  
Biomedical Literature ◽  
Malignant Neoplasms ◽  
Protein Protein Interactions ◽  
Protein Protein Interaction ◽  
Interaction Database ◽  
Protein Interaction Database

Abstract Background Protein–protein interaction (PPI) information extraction from biomedical literature helps unveil the molecular mechanisms of biological processes. Especially, the PPIs associated with human malignant neoplasms can unveil the biology behind these neoplasms. However, such PPI database is not currently available. Results In this work, a database of protein–protein interactions associated with 171 kinds of human malignant neoplasms named HMNPPID is constructed. In addition, a visualization program, named VisualPPI, is provided to facilitate the analysis of the PPI network for a specific neoplasm. Conclusions HMNPPID can hopefully become an important resource for the research on PPIs of human malignant neoplasms since it provides readily available data for healthcare professionals. Thus, they do not need to dig into a large amount of biomedical literatures any more, which may accelerate the researches on the PPIs of malignant neoplasms.

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