Part of the book series:Lecture Notes in Computer Science ((LNISA,volume 6335))
Included in the following conference series:
Abstract
Protein Sub-cellular Localization (PSL) prediction is an important task for predicting protein functions. Because the sequence-based approach used in the most previous work has focused on prediction of locations for given proteins, it failed to provide useful information for the cases in which single proteins are localized, depending on their states in progress, in several different sub-cellular locations. While it is difficult for the sequence-based approach, it can be tackled by the text-based approach.
The proposed approach extracts PSL from literature using Natural Language Processing techniques. We conducted experiments to see how our system performs in identification of evidence sentences and what linguistic features from sentences significantly contribute to the task. This article presents a text-based novel approach to extract PSL relations with their evidence sentences. Evidence sentences will provide indispensable pieces of information that the sequence-based approach cannot supply.
This is a preview of subscription content,log in via an institution to check access.
Access this chapter
Subscribe and save
- Get 10 units per month
- Download Article/Chapter or eBook
- 1 Unit = 1 Article or 1 Chapter
- Cancel anytime
Buy Now
- Chapter
- JPY 3498
- Price includes VAT (Japan)
- eBook
- JPY 5719
- Price includes VAT (Japan)
- Softcover Book
- JPY 7149
- Price includes VAT (Japan)
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Horton, P., Park, K.J., Obayashi, T., Nakai, K.: Protein Subcellular Localization Prediction with WoLF PSORT. In: Asia Pacific Bioinformatics Conference (APBC), pp. 39–48 (2006)
Stapley, B.J., Kelley, L., Sternberg, M.: Predicting the subcellular location of proteins from text using support vector machines. In: Pacic Symposium on Biocomputing, PSB (2002)
Brady, S., Shatkay, H.: EPILOC: A (Working) Text-Based System for Predicting Protein Subcellular Location. In: Pacific Symposium on Biocomputing, PSB (2008)
Kim, J.D., Ohta, T., Tsujii, J.: Corpus annotation for mining biomedical events from literature. BMC Bioinformatics 9(10) (2008)
Sim, J., Wright, C.C.: The Kappa Statistic in Reliability Studies: Use, Interpretation, and Sample Size Requirements. Physical Therapy 85(3), 206–282 (2005)
Landis, J.R., Koch, G.G.: The measurement of observer agreement for categorical data. Biometrics 33, 159–174 (1977)
Berger, A.L., Della Pietra, S.A., Della Pietra, V.J.: A maximum entropy approach to natural language processing. Computational Linguistics 22(1), 39–71 (1996)
Tsujii Laboratory: ENJU Deep Syntactic Full Parser ver. 2.1.,http://www-tsujii.is.s.u-tokyo.ac.jp/enju/index.html/
Tsujii Laboratory: GENIA Project,http://www-tsujii.is.s.u-tokyo.ac.jp/GENIA/
Author information
Authors and Affiliations
Korea Institute of Science and Technology Information, 335 Gwahangno, Yuseong-gu, Daejeon, 305-806, Republic of Korea
Hong-Woo Chun, Yun-Soo Choi & Won-Kyung Sung
Database Center for Life Science, Research Organization of Information and System, Japan
Jin-Dong Kim
- Hong-Woo Chun
You can also search for this author inPubMed Google Scholar
- Jin-Dong Kim
You can also search for this author inPubMed Google Scholar
- Yun-Soo Choi
You can also search for this author inPubMed Google Scholar
- Won-Kyung Sung
You can also search for this author inPubMed Google Scholar
Editor information
Editors and Affiliations
Department of Computer Science and Engineering, York University, M3J 1P3, Toronto, ON, Canada
Aijun An
Department of Mathematics and Computing Science, Saint Mary’s University, B3H 3C3, Halifax, NS, Canada
Pawan Lingras
Faculty of Fine Arts, University of Regina, 3737 Wascana Parkway, S4S 0A2, Regina, SK, Canada
Sheila Petty
Faculty of Computer and Information Sciences, Hosei University, 3-7-2, Kajino-cho, Koganei-shi, 184-8584, Tokyo, Japan
Runhe Huang
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Chun, HW., Kim, JD., Choi, YS., Sung, WK. (2010). Extracting Protein Sub-cellular Localizations from Literature. In: An, A., Lingras, P., Petty, S., Huang, R. (eds) Active Media Technology. AMT 2010. Lecture Notes in Computer Science, vol 6335. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15470-6_39
Download citation
Publisher Name:Springer, Berlin, Heidelberg
Print ISBN:978-3-642-15469-0
Online ISBN:978-3-642-15470-6
eBook Packages:Computer ScienceComputer Science (R0)
Share this paper
Anyone you share the following link with will be able to read this content:
Sorry, a shareable link is not currently available for this article.
Provided by the Springer Nature SharedIt content-sharing initiative