Understanding gene expression is an important factor for cancer diagnosis. One target of this understanding is implementing cancer gene search and classification methods. However, cancer gene search and classification is a challenge in that there is no obvious exact algorithm that can be implemented individually for various cancer cells. In this paper, a research is conducted through the most common top-ranked algorithms implemented for cancer gene search and classification, and on how they are implemented to reach a better performance. The paper will distinguish algorithms implemented for bio-image analysis for cancer cells and algorithms implemented based on DNA microarray data. The paper will also explore the road map towards presenting the most current algorithms implemented for cancer gene search and classification, as well as focusing on the importance of search algorithms and how they are implemented to enhance search and the factors that affect the performance.
|Number of pages||18|
|Journal||International Journal of Data Mining and Bioinformatics|
|Early online date||12 Feb 2016|
|Publication status||Published - 2016|