A Survey on Gene Selection for Microarray Cancer Classification Based on Soft Computing Techniques

Recent developments in the field of soft computing have affected a large number of research works of data mining in a positive way. Processing and analysis of large data become an easy task when using soft computing techniques and especially for NP-Complete problems. This paper focuses on the cancer classification field which is an important research field in Bioinformatics. The efficiency in cancer classification depends on the competence in selecting the most promising genes using a suitable gene selection algorithm. By using soft computing techniques, the performances of gene selection algorithms are enhanced and efficient results are obtained. In this paper, a detailed literature has been done on gene selection and cancer classification and a detailed review have been made on the various gene selection algorithms based on soft computing techniques. A comparison is made based on different aspects of the existing gene selection algorithms. Apart from this, the future of gene selection and classification along with the various research gaps has been discussed.