Title :
MinePhos: A Literature Mining System for Protein Phoshphorylation Information Extraction
Author :
Yun Xu ; Da Teng ; Yiming Lei
Author_Institution :
Anhui Province Key Lab. of High Performance Comput., Univ. of Sci. & Technol. of China, Hefei, China
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.
Keywords :
biochemistry; bioinformatics; cellular biophysics; data mining; molecular biophysics; proteins; support vector machines; MinePhos; RLIMS-P; SVM-based system; cellular process; data extraction; diseases; protein phosphorylation information extraction; Abstracts; Bioinformatics; Data mining; Databases; Dictionaries; Proteins; Substrates; Phospho.ELM; Phosphrylation; SVM; literature mining.; Computational Biology; Data Mining; Databases, Protein; Phosphorylation; Phosphotransferases; Proteins; Reproducibility of Results; Support Vector Machines;
Journal_Title :
Computational Biology and Bioinformatics, IEEE/ACM Transactions on
DOI :
10.1109/TCBB.2011.85
