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Small-to-medium enterprises (SMEs) in regional (non-metropolitan) areas are considered when economic planning may require large data sets and sophisticated clustering techniques. The economic growth of regional areas was investigated using four clustering algorithms. Empirical analysis demonstrated that the modified global k-means algorithm outperformed other algorithms.

Although research has examined population growth and decline using functional specialisation, little attention has been paid to the possible combined effects of functional specialisation and socio-economic factors on population change. Using the Australian Bureau of Statistics Census Data 2001–2006 for statistical local areas, this study presents an investigation of the role of both functional specialisation and socio-economic factors in population change in non-metropolitan areas under the sustenance framework. The uniqueness of the study is twofold. Conceptually it develops a framework to compare the combined role of functional specialisation and socio-economic factors on population change; and, empirically it uses data mining (cluster analysis) techniques to investigate the extent of this combined role. The results show the significance of both functional specialisation and socio-economic factors. Policy implications of the study indicate the need to examine regional development and population change in relation to functional specialisation and socio-economic factors and their impact on viability of non-metropolitan areas.

Bioinformatics is an interdisciplinary research field that combines biology, computer science, mathematics and statistics into a broad-based field that will have profound impacts on all fields of biology. The emphasis of IJBRA is on basic bioinformatics research methods, tool development, performance evaluation and their applications in biology. IJBRA addresses the most innovative developments, research issues and solutions in bioinformatics and computational biology and their applications.