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PHRP : Osong Public Health and Research Perspectives

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Original Article
Predicting 5-Year Survival Status of Patients with Breast Cancer based on Supervised Wavelet Method
Maryam Farhadian, Hossein Mahjub, Jalal Poorolajal, Abbas Moghimbeigi, Muharram Mansoorizadeh
Osong Public Health Res Perspect. 2014;5(6):324-332.   Published online December 31, 2014
DOI: https://doi.org/10.1016/j.phrp.2014.09.002
  • 2,771 View
  • 19 Download
  • 4 Crossref
AbstractAbstract PDF
Objectives
Classification of breast cancer patients into different risk classes is very important in clinical applications. It is estimated that the advent of high-dimensional gene expression data could improve patient classification. In this study, a new method for transforming the high-dimensional gene expression data in a low-dimensional space based on wavelet transform (WT) is presented.
Methods
The proposed method was applied to three publicly available microarray data sets. After dimensionality reduction using supervised wavelet, a predictive support vector machine (SVM) model was built upon the reduced dimensional space. In addition, the proposed method was compared with the supervised principal component analysis (PCA).
Results
The performance of supervised wavelet and supervised PCA based on selected genes were better than the signature genes identified in the other studies. Furthermore, the supervised wavelet method generally performed better than the supervised PCA for predicting the 5-year survival status of patients with breast cancer based on microarray data. In addition, the proposed method had a relatively acceptable performance compared with the other studies.
Conclusion
The results suggest the possibility of developing a new tool using wavelets for the dimension reduction of microarray data sets in the classification framework.

Citations

Citations to this article as recorded by  
  • Diagnosing thyroid disorders: Comparison of logistic regression and neural network models
    Shiva Borzouei, Hossein Mahjub, NegarAsaad Sajadi, Maryam Farhadian
    Journal of Family Medicine and Primary Care.2020; 9(3): 1470.     CrossRef
  • Thyroid disorder diagnosis based on Mamdani fuzzy inference system classifier
    Negar Asaad Sajadi, Hossein Mahjub, Shiva Borzouei, Maryam Farhadian
    Koomesh Journal.2020; 22(1): 107.     CrossRef
  • Diagnosis of hypothyroidism using a fuzzy rule-based expert system
    Negar Asaad Sajadi, Shiva Borzouei, Hossein Mahjub, Maryam Farhadian
    Clinical Epidemiology and Global Health.2019; 7(4): 519.     CrossRef
  • WaveICA: A novel algorithm to remove batch effects for large-scale untargeted metabolomics data based on wavelet analysis
    Kui Deng, Fan Zhang, Qilong Tan, Yue Huang, Wei Song, Zhiwei Rong, Zheng-Jiang Zhu, Kang Li, Zhenzi Li
    Analytica Chimica Acta.2019; 1061: 60.     CrossRef
Article
Enhanced Type III Secretion System Expression of Atypical Shigella flexneri II:(3)4,7(8)
Sahyun Hong, Injun Cha, Nan-Ok Kim, Seong-Han Kim, Kyung-Tae Jung, Je-Hee Lee, Dong-Wook Kim, Mi-Sun Park, Yeon-Ho Kang
Osong Public Health Res Perspect. 2012;3(4):222-228.   Published online December 31, 2012
DOI: https://doi.org/10.1016/j.phrp.2012.10.002
  • 2,543 View
  • 19 Download
AbstractAbstract PDF
Objectives
We aimed at evaluating the virulence of atypical Shigella flexneri II:(3)4,7(8) by DNA microarray and invasion assay.
Methods
We used a customized S. flexneri DNA microarray to analyze an atypical S. flexneri II:(3)4,7(8) gene expression profile and compared it with that of the S. flexneri 2b strain.
Results
Approximately one-quarter of the atypical S. flexneri II:(3)4,7(8) strain genes showed significantly altered expression profiles; 344 genes were more than two-fold upregulated, and 442 genes were more than 0.5-fold downregulated. The upregulated genes were divided into the category of 21 clusters of orthologous groups (COGs), and the “not in COGs” category included 170 genes. This category had virulence plasmid genes, including the ipa-mxi-spa genes required for invasion of colorectal epithelium (type III secretion system). Quantitative reverse-transcription polymerase chain reaction results also showed the same pattern in two more atypical S. flexneri II:(3)4,7(8) strains. Atypical S. flexneri II:(3)4,7(8) showed four times increased invasion activity in Caco-2 cells than that of typical strains.
Conclusion
Our results provide the intracellularly regulated genes that may be important for adaptation and growth strategies of this atypical S. flexneri.

PHRP : Osong Public Health and Research Perspectives