The week's pick
Random Articles
Reseach Article
Predicting Cancer-Related Proteins in Protein-Protein Interaction Networks using Network Approach and SMO-SVM Algorithm
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 115 - Number 3 |
| Year of Publication: 2015 |
| Authors: Richard Enyinnaya |
10.5120/20129-2212
|
Richard Enyinnaya . Predicting Cancer-Related Proteins in Protein-Protein Interaction Networks using Network Approach and SMO-SVM Algorithm. International Journal of Computer Applications. 115, 3 ( April 2015), 5-9. DOI=10.5120/20129-2212
Abstract
An early diagnosis of cancer is crucial to improving the survival rate and to prolong the lives of patients. With the large amounts of medical data available in the medical field, applying data mining tools and an efficient prediction methodology to diagnose diseases can lead to useful knowledge to support medical professionals in saving lives. This paper explores genomic interactions networks, investigating protein-protein interaction networks to predict cancer related proteins using sequential minimal Optimization (SMO) for training Support Vector Machine (SVM). The WEKA software was utilized as the data mining tool, which is an open source collection of machine learning algorithms. The provided data set was studied and analyzed in order to build a useful and reliable model to predict cancer and non-cancer related proteins.
References
- Wu, Xuebing, and Shao Li. "Cancer gene prediction using a network approach. " Cancer Systems Biology (2010): 191-212.
- Lin, C. , Cho, Y. R. , Hwang, W. C. , Pei, P. , & Zhang, A. (2007). Clustering methods in protein-protein interaction network. Knowledge Discovery in Bioinformatics: Techniques, Methods and Application, 1-35.
- Platt, John. "Sequential minimal optimization: A fast algorithm for training support vector machines. " (1998).
- Hardin, Douglas, Isabelle Guyon, and Constantin F. Aliferis. A Gentle Introduction to Support Vector Machines in Biomedicine. World Scientific, 2011.
- Hu, Yifan. "Efficient, high-quality force-directed graph drawing. " Mathematica Journal 10. 1 (2005): 37-71.
- Yang, Lei, Xudong Zhao, and Xianglong Tang. "Predicting Disease-Related Proteins Based on Clique Backbone in Protein-Protein Interaction Network. " International journal of biological sciences 10. 7 (2014): 677.
- "Tumor - Nutrients. " NetLogo User Community Models. NetLogo, 27 Dec. 2008. Web. 2 Jan. 2015.
- Schwikowski, Benno, Peter Uetz, and Stanley Fields. "A network of protein–protein interactions in yeast. " Nature biotechnology 18. 12 (2000): 1257-1261
- Cardelli, Luca. "Abstract machines of systems biology. " Transactions on Computational Systems Biology III. Springer Berlin Heidelberg, 2005. 145-168.
- Barabási,Albert-László,Natali Gulbahce, and Joseph Loscalzo. "Network medicine: a network-based approach to human disease. " Nature Reviews Genetics 12. 1 (2011): 56-68.
- Ergün, A. , Lawrence, C. A. , Kohanski, M. A. , Brennan, T. A. , & Collins, J. J. (2007). A network biology approach to prostate cancer. Molecular systems biology, 3(1), 82.
- George, G. , and V. Cyril Raj. "Review on feature selection techniques and the impact of SVM for cancer classification using gene expression profile. " arXiv preprint arXiv:1109. 1062 (2011).
- Guyon, I. , Weston, J. , Barnhill, S. , & Vapnik, V. (2002). Gene selection for cancer classification using support vector machines. Machine learning, 46(1-3), 389-422.
- Lo, J. Y. , Baker, J. A. , Kornguth, P. J. , & Floyd, C. E. (1995). Computer-aided diagnosis of breast cancer: artificial neural network approach for optimized merging of mammographic features. Academic radiology, 2(10), 841-850.
- Chuang, H. Y. , Lee, E. , Liu, Y. T. , Lee, D. , & Ideker, T. (2007). Network?based classification of breast cancer metastasis. Molecular systems biology, 3(1).
- Janghel, R. R. , Shukla, A. , Tiwari, R. , & Kala, R. (2010, June). Breast cancer diagnosis using artificial neural network models. In Information Sciences and Interaction Sciences (ICIS), 2010 3rd International Conference on (pp. 89-94). IEEE.
- Polat, Kemal, and Salih Günes. "Breast cancer diagnosis using least square support vector machine. " Digital Signal Processing 17. 4 (2007): 694-701.
- Yu, W. , He, L. R. , Zhao, Y. C. , Chan, M. H. , Zhang, M. , & He, M. (2013). Dynamic protein-protein interaction subnetworks of lung cancer in cases with smoking history. Chinese journal of cancer, 32(2), 84.
- Powers, David Martin. "Evaluation: from precision, recall and F-measure to ROC, informedness, markedness and correlation. " (2011).
- Huang, C. H. , Peng, H. S. , & Ng, K. L. (2015). Prediction of Cancer Proteins by Integrating Protein Interaction, Domain Frequency, and Domain Interaction Data Using Machine Learning Algorithms. BioMed Research International, 2015.
Index Terms
Keywords