Obesity is a complex disorder resulting from the interplay of genetic, environmental,
behavioral factors and life style and has a significant impact on the public health. The complexity of
the disorder entails multidisciplinary research efforts involving various research disciplines to
enhance the understanding of the molecular mechanisms implicated in the development of the
disease. The disruption of the balance between energy intake and energy expenditure which leads to
obesity involves the action of many contributing factors and many molecular compounds, making
high-dimensional profiling very attractive. Nonetheless, despite definite advances in omics research
over the last decade, many challenges remain, including combining data from the heterogeneous
sources, development of data mining tools, and integrative analysis methodologies to fully exploit
various hypotheses. This review presents a brief overview of ongoing research, summarizes current
methodologies, techniques, and challenges in omics approaches to obesity research, and identifies
areas of further research.
Keywords: Omics, heterogeneous types of data, integrative approaches, statistical issues.
