Much can be learned about the progress, fathers and future
of a scientific domain from the analysis of a collection of relevant
articles and their corresponding authors. Here, we study the highly interdisciplinary
domain of Artificial Immune System (AIS) since its birth,
a couple of decades ago. We apply Social Network Analysis to the coauthorship
network of the most comprehensive publicly accessible AIS
bibliography. We automatically extract publication dates and author
names from the bibliography and evaluate authors with the highest degree
(unique collaborations) and centrality (influence).
Our results highlight the relative growth of publication volume and identify
significant contributors in the AIS field. Furthermore, our findings
are not only encouraging for the AIS community but may be useful for
analyses of other scientific communities and leading contributors therein.