Negative Selection

Distributed Black-Box Software Testing Using Negative Selection

In the software development process, testing is one of the most human intensive steps. Many researchers try to automate test case generation to reduce the manual labor of this step. Negative selection is a famous algorithm in the field of Artificial Immune System (AIS) and many different applications has been developed using its idea. In this paper we have designed a new algorithm based on nega...

Negative Selection Based Data Classification with Flexible Boundaries

One of the most important artificial immune algorithms is negative selection algorithm, which is an anomaly detection and pattern recognition technique; however, recent research has shown the successful application of this algorithm in data classification. Most of the negative selection methods consider deterministic boundaries to distinguish between self and non-self-spaces. In this paper, two...

Revisiting Negative Selection Algorithms

This paper reviews the progress of negative selection algorithms, an anomaly/change detection approach in Artificial Immune Systems (AIS). Following its initial model, we try to identify the fundamental characteristics of this family of algorithms and summarize their diversities. There exist various elements in this method, including data representation, coverage estimate, affinity measure, and...

Negative Selection by IgM Superantigen

Detecting Past Positive Selection through Ongoing Negative Selection

Detecting positive selection is a challenging task. We propose a method for detecting past positive selection through ongoing negative selection, based on comparison of the parameters of intraspecies polymorphism at functionally important and selectively neutral sites where a nucleotide substitution of the same kind occurred recently. Reduced occurrence of recently replaced ancestral alleles at...