Literature DB >> 21576755

MinePhos: a literature mining system for protein phoshphorylation information extraction.

Yun Xu1, Da Teng, Yiming Lei.   

Abstract

The rapid growth of scientific literature calls for automatic and efficient ways to facilitate extracting experimental data on protein phosphorylation. Such information is of great value for biologists in studying cellular processes and diseases such as cancer and diabetes. Existing approaches like RLIMS-P are mainly rule based. The performance lays much reliance on the completeness of rules. We propose an SVM-based system known as MinePhos which outperforms RLIMS-P in both precision and recall of information extraction when tested on a set of articles randomly chosen from PubMed.

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Year:  2011        PMID: 21576755     DOI: 10.1109/TCBB.2011.85

Source DB:  PubMed          Journal:  IEEE/ACM Trans Comput Biol Bioinform        ISSN: 1545-5963            Impact factor:   3.710


  5 in total

1.  RLIMS-P 2.0: A Generalizable Rule-Based Information Extraction System for Literature Mining of Protein Phosphorylation Information.

Authors:  Manabu Torii; Cecilia N Arighi; Gang Li; Qinghua Wang; Cathy H Wu; K Vijay-Shanker
Journal:  IEEE/ACM Trans Comput Biol Bioinform       Date:  2015 Jan-Feb       Impact factor: 3.710

2.  Text Mining and Machine Learning Protocol for Extracting Human-Related Protein Phosphorylation Information from PubMed.

Authors:  Krishnamurthy Arumugam; Raja Ravi Shanker
Journal:  Methods Mol Biol       Date:  2022

3.  Application of text-mining for updating protein post-translational modification annotation in UniProtKB.

Authors:  Anne-Lise Veuthey; Alan Bridge; Julien Gobeill; Patrick Ruch; Johanna R McEntyre; Lydie Bougueleret; Ioannis Xenarios
Journal:  BMC Bioinformatics       Date:  2013-03-22       Impact factor: 3.169

4.  Construction of phosphorylation interaction networks by text mining of full-length articles using the eFIP system.

Authors:  Catalina O Tudor; Karen E Ross; Gang Li; K Vijay-Shanker; Cathy H Wu; Cecilia N Arighi
Journal:  Database (Oxford)       Date:  2015-03-31       Impact factor: 3.451

5.  The eFIP system for text mining of protein interaction networks of phosphorylated proteins.

Authors:  Catalina O Tudor; Cecilia N Arighi; Qinghua Wang; Cathy H Wu; K Vijay-Shanker
Journal:  Database (Oxford)       Date:  2012-12-05       Impact factor: 3.451

  5 in total

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