Disparity-filtered differential correlation network analysis: a case study on CRC metabolomics

Differential network analysis has become a widely used technique to investigate changes of interactions among different conditions. Although the relationship between observed interactions and biochemical mechanisms is hard to establish, differential network analysis can provide useful insights about dysregulated pathways and candidate biomarkers. The available methods to detect differential interactions are heterogeneous and often rely on assumptions that are unrealistic in many applications. To address these issues, we develop a novel method for differential network analysis, using the so-called disparity filter as network reduction technique. In addition, we propose a classification model based on the inferred network interactions. The main novelty of this work lies in its ability to preserve connections that are statistically significant with respect to a null model without favouring any resolution scale, as a hard threshold would do, and without Gaussian assumptions. The method was tested using a published metabolomic dataset on colorectal cancer (CRC). Detected hub metabolites were consistent with recent literature and the classifier was able to distinguish CRC from polyp and healthy subjects with great accuracy. In conclusion, the proposed method provides a new simple and effective framework for the identification of differential interaction patterns and improves the biological interpretation of metabolomics data.

A simple network reduction technique for large autonomous microgrids incorporating an efficient reactive power sharing

Reactive power sharing continues to be a challenge for an autonomous Microgrid (MG) since reactive power sharing is largely affected by the mismatch in line impedance and the asymmetry of local loads. Several reactive power sharing methods have been proposed in an autonomous MG but their effectiveness on large MG systems has not been explored much. This paper considers a standard IEEE 38 bus autonomous MG to study the effectiveness of proportionate power sharing. A simple network reduction technique has been proposed to obtain an equivalent reduced MG for which a reactive power sharing technique is applied. The most feasible method has been analyzed and the communication based reactive power sharing along with droop controller is proved to be the popular and most generalized strategy for effective power sharing. MATLAB-Simulink tool is used to validate the power sharing with equal and unequal DG ratings in a standard IEEE 38 bus autonomous MG system with network reduction.