DocumentCode :
191022
Title :
Identification of protein interaction methods from biomedical literature
Author :
Jhamb, Deepali ; Krishnan, Arjun ; Palakal, Mathew ; Pandit, Yogesh ; Palakal, Mathew J. ; Duraiswamy, Premkumar
Author_Institution :
Sch. of Inf. & Comput., Indiana Univ. - Purdue Univ., Indianapolis, IN, USA
fYear :
2014
fDate :
2-4 June 2014
Firstpage :
1
Lastpage :
6
Abstract :
Proteins are the functional subunits of a cell which interact with each other to carry out biological processes. Protein interaction networks form the backbone of the research in molecular and systems biology. Although there are available methods to mine protein interactions and their detection methods from the biological literature, the accuracy of these methods is quite low. In this study, we applied regular expressions to identify the three most frequent protein interaction detection methods from the methodology section of the full text articles. These articles were then further used to extract the protein protein interactions. We report an overall specificity of 83.6 and sensitivity of 78.2 for the identification of interaction methods.
Keywords :
biology computing; cellular biophysics; data mining; molecular biophysics; proteins; text analysis; biological processes; biomedical literature; cellular biophysics; data mining; functional subunits; molecular systems; protein-protein interaction detection methods; regular expressions; text analysis; Accuracy; Databases; Manuals; Protein engineering; Proteins; Support vector machines; data mining; protein interaction; protein interaction detection method; regex;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Advances in Bio and Medical Sciences (ICCABS), 2014 IEEE 4th International Conference on
Conference_Location :
Miami, FL
Print_ISBN :
978-1-4799-5786-6
Type :
conf
DOI :
10.1109/ICCABS.2014.6863923
Filename :
6863923
Link To Document :
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