[Purpose] To find the physical activity level and fall risk among the community-dwelling Malaysian older adults and determine the correlation between them. [Subjects and Methods] A cross-sectional study was conducted in which, the physical activity level was evaluated using the Rapid Assessment of Physical Activity questionnaire and fall risk with Fall Risk Assessment Tool. Subjects recruited were 132 community-dwelling Malaysian older adults using the convenience sampling method. [Results] The majority of the participants were under the category of under-active regular light-activities and most of them reported low fall risk. The statistical analysis using Fisher's exact test did not show a significant correlation between physical activity level and fall risk. [Conclusion] The majority of community-dwelling Malaysian older adults are performing some form of physical activity and in low fall risk category. But this study did not find any significant correlation between physical activity level and fall risk among community-dwelling older adults in Malaysia.
Many biological research areas such as drug design require gene regulatory networks to provide clear insight and understanding of the cellular process in living cells. This is because interactions among the genes and their products play an important role in many molecular processes. A gene regulatory network can act as a blueprint for the researchers to observe the relationships among genes. Due to its importance, several computational approaches have been proposed to infer gene regulatory networks from gene expression data. In this review, six inference approaches are discussed: Boolean network, probabilistic Boolean network, ordinary differential equation, neural network, Bayesian network, and dynamic Bayesian network. These approaches are discussed in terms of introduction, methodology and recent applications of these approaches in gene regulatory network construction. These approaches are also compared in the discussion section. Furthermore, the strengths and weaknesses of these computational approaches are described.