scholarly journals Novel approach to protein-protein interaction assessment

2020 ◽  
Vol 548 ◽  
pp. 072046
Author(s):  
F N Gilmiyarova ◽  
N A Kolotyeva ◽  
V I Kuzmicheva ◽  
V V Remizov ◽  
O A Gusyakova
Keyword(s):  
Protein Interaction ◽  
Protein Protein Interaction ◽  
Novel Approach

scholarly journals A Novel Approach for Protein-Named Entity Recognition and Protein-Protein Interaction Extraction

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Meijing Li ◽  
Tsendsuren Munkhdalai ◽  
Xiuming Yu ◽  
Keun Ho Ryu
Keyword(s):  
Language Processing ◽  
Protein Interaction ◽  
Named Entity Recognition ◽  
Entity Recognition ◽  
Support Vector ◽  
Protein Protein Interaction ◽  
Named Entity ◽  
Novel Approach ◽  
Interaction Extraction ◽  
Parsing Tree

Many researchers focus on developing protein-named entity recognition (Protein-NER) or PPI extraction systems. However, the studies about these two topics cannot be merged well; then existing PPI extraction systems’ Protein-NER still needs to improve. In this paper, we developed the protein-protein interaction extraction system named PPIMiner based on Support Vector Machine (SVM) and parsing tree. PPIMiner consists of three main models: natural language processing (NLP) model, Protein-NER model, and PPI discovery model. The Protein-NER model, which is named ProNER, identifies the protein names based on two methods: dictionary-based method and machine learning-based method. ProNER is capable of identifying more proteins than dictionary-based Protein-NER model in other existing systems. The final discovered PPIs extracted via PPI discovery model are represented in detail because we showed the protein interaction types and the occurrence frequency through two different methods. In the experiments, the result shows that the performances achieved by our ProNER and PPI discovery model are better than other existing tools. PPIMiner applied this protein-named entity recognition approach and parsing tree based PPI extraction method to improve the performance of PPI extraction. We also provide an easy-to-use interface to access PPIs database and an online system for PPIs extraction and Protein-NER.

An efficient transient assays system using Agrobacterium-mediated transformation of onion (Allium cepa) epidermal cells

2020 ◽  
Vol 80 (03) ◽  
Author(s):  
Yu-Miao Zhang ◽  
Jun Wang ◽  
Tao Wu
Keyword(s):  
Subcellular Localization ◽  
Protein Interaction ◽  
Protein Interactions ◽  
Epidermal Cells ◽  
Cyclin Dependent Kinase ◽  
Protein Subcellular Localization ◽  
Protein Protein Interactions ◽  
Efficient System ◽  
Protein Protein Interaction ◽  
Onion Epidermal Cells

In this study, the Agrobacterium infection medium, infection duration, detergent, and cell density were optimized. The sorghum-based infection medium (SbIM), 10-20 min infection time, addition of 0.01% Silwet L-77, and Agrobacterium optical density at 600 nm (OD600), improved the competence of onion epidermal cells to support Agrobacterium infection at >90% efficiency. Cyclin-dependent kinase D-2 (CDKD-2) and cytochrome c-type biogenesis protein (CYCH), protein-protein interactions were localized. The optimized procedure is a quick and efficient system for examining protein subcellular localization and protein-protein interaction.

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