An artificial immune system-based algorithm for abnormal pattern in medical domain.

In general, medical pattern is a collection of characters formed using the characters such as 'a', 'c', 'g' and 't'. The length of the pattern varies from one disease to another disease, and the pattern also seems to be different for different patients. Identifying an unusual pattern from the information design is troublesome a decade ago. In this paper, with a specific end goal to enhance the precision of the anomalous distinguishing pattern, an Artificial Immune System (AIS) is framed. In the present study, AIS is used to obtain the abnormal pattern by learning the characteristics of the entire data set. Due to the powerful and adaptive nature of AIS, detecting and identifying abnormal pattern is more accurate. This proposed idea is implemented in MATLAB software and experimented on DNA/RNA dataset and the performance is verified. [ABSTRACT FROM AUTHOR]