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Prediction of Cancer Proteins by Integrating Protein Interaction, Domain Frequency, and Domain Interaction Data Using Machine Learning Algorithms
Joint Authors
Peng, Huai-Shun
Huang, Chien-Hung
Ng, Ka-Lok
Source
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-15, 15 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-03-17
Country of Publication
Egypt
No. of Pages
15
Main Subjects
Abstract EN
Many proteins are known to be associated with cancer diseases.
It is quite often that their precise functional role in disease pathogenesis remains unclear.
A strategy to gain a better understanding of the function of these proteins is to make use of a combination of different aspects of proteomics data types.
In this study, we extended Aragues’s method by employing the protein-protein interaction (PPI) data, domain-domain interaction (DDI) data, weighted domain frequency score (DFS), and cancer linker degree (CLD) data to predict cancer proteins.
Performances were benchmarked based on three kinds of experiments as follows: (I) using individual algorithm, (II) combining algorithms, and (III) combining the same classification types of algorithms.
When compared with Aragues’s method, our proposed methods, that is, machine learning algorithm and voting with the majority, are significantly superior in all seven performance measures.
We demonstrated the accuracy of the proposed method on two independent datasets.
The best algorithm can achieve a hit ratio of 89.4% and 72.8% for lung cancer dataset and lung cancer microarray study, respectively.
It is anticipated that the current research could help understand disease mechanisms and diagnosis.
American Psychological Association (APA)
Huang, Chien-Hung& Peng, Huai-Shun& Ng, Ka-Lok. 2015. Prediction of Cancer Proteins by Integrating Protein Interaction, Domain Frequency, and Domain Interaction Data Using Machine Learning Algorithms. BioMed Research International،Vol. 2015, no. 2015, pp.1-15.
https://search.emarefa.net/detail/BIM-1055000
Modern Language Association (MLA)
Huang, Chien-Hung…[et al.]. Prediction of Cancer Proteins by Integrating Protein Interaction, Domain Frequency, and Domain Interaction Data Using Machine Learning Algorithms. BioMed Research International No. 2015 (2015), pp.1-15.
https://search.emarefa.net/detail/BIM-1055000
American Medical Association (AMA)
Huang, Chien-Hung& Peng, Huai-Shun& Ng, Ka-Lok. Prediction of Cancer Proteins by Integrating Protein Interaction, Domain Frequency, and Domain Interaction Data Using Machine Learning Algorithms. BioMed Research International. 2015. Vol. 2015, no. 2015, pp.1-15.
https://search.emarefa.net/detail/BIM-1055000
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1055000