A Model Based Approach On Gene Expression Profiling Of Colorectal Cancer And Normal Mucosa Using Logistic Regression, Artificial Neural Network And Structural Equation Modelling
Main Article Content
Abstract
Colorectal cancer is one of the leading biomedical issues of concern. Our understanding of the disease has improved using microarray expression data analysis over last few decades. Therefore, it is of interest to design conceptual statistical models to analyze volumes of data to glean useful information. We used data from the open source Gene Expression Omnibus database containing information on160 normal mucosa tissues and 203 CRCs. The model described in this report selected 44 candidate genes exceeding 4-fold threshold expression. The reliability was determined using Cronbach’s alpha measurement for further statistical analysis. Structural Equation Modelling and binary logistic regression and neural networks were used to incur the strength of association of genes with the disease outcome.
Downloads
Metrics
Article Details
You are free to:
- Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
- The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
- Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices:
You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation .
No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.