Algorithms Implemented for Cancer Gene Searching and Classifications

Abstract

Abstract. Understanding the gene expression is an important factor to 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 an 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 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 array data. The main purpose of this paper is to explore a road map towards presenting the most current algorithms implemented for cancer gene search and classification.

Examining applying high performance genetic data feature selection and classification algorithms for colon cancer diagnosis

“…Also, the authors in [55] exposed the highest accuracy for colon cancer classification found by KNN (K-Nearest Neighbors) and Neural Network classifier among other classification algorithms, however they claimed out that other optimization techniques can be added to classification algorithms. Many algorithms have been implemented for the selection and classification of cancer genes [29]. These include Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Analysis of Variance (ANOVA), Information Gain (IG), Relief Algorithm (RA), and t-statistics (TA).…”

“…These include Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Analysis of Variance (ANOVA), Information Gain (IG), Relief Algorithm (RA), and t-statistics (TA). The classification algorithms that exhibit good performance are Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Naïve Bayes, Neural Networks (NN), and Decision Tree (DT) [29]. Many studies have been conducted to study the process of cancer classification using microarray genetic data, including colon cancer.…”