Kernel-based visualisation of genes with the gene ontology

With the development of microarray-based high- throughput technologies for examining genetic and biological information en masse, biologists are now faced with making sense of large lists of genes identi-ffed from their biological experiments. There is a vital need for \system biology" approaches which can allow biologists to see new or unanticipated potential relationships which will lead to new hypotheses and eventual new knowledge. Finding and understanding relationships in this data is a problem well suited to visualisation. We augment genes with their associated terms from the Gene Ontology and visualise them using kernel Principal Component Analysis with both specialised linear and Gaussian kernels. Our results show that this method can correctly visualise genes by their functional relationships and we describe the difference between using the linear and Gaussian kernels on the problem. © 2008, Australian Computer Society, Inc

Finite-region stabilization via dynamic output feedback for 2-D Roesser models

Finite-region stability (FRS), a generalization of finite-time stability, has been used to analyze the transient behavior of discrete two-dimensional (2-D) systems. In this paper, we consider the problem of FRS for discrete 2-D Roesser models via dynamic output feedback. First, a sufficient condition is given to design the dynamic output feedback controller with a state feedback-observer structure, which ensures the closed-loop system FRS. Then, this condition is reducible to a condition that is solvable by linear matrix inequalities. Finally, viable experimental results are demonstrated by an illustrative example

Antiglycation and antioxidant properties of Momordica charantia

The accumulation of advanced glycation endproducts (AGEs) and oxidative stress underlie the pathogenesis of diabetic complications. In many developing countries, diabetes treatment is unaffordable, and plants such as bitter gourd (or bitter melon; Momordica charantia) are used as traditional remedies because they exhibit hypoglycaemic properties. This study compared the antiglycation and antioxidant properties of aqueous extracts of M. charantia pulp (MCP), flesh (MCF) and charantin in vitro. Lysozyme was mixed with methylglyoxal and 0–15 mg/ml of M. charantia extracts in a pH 7.4 buffer and incubated at 37°C for 3 days. Crosslinked AGEs were assessed using gel electrophoresis, and the carboxymethyllysine (CML) content was analyzed by enzyme-linked immunosorbent assays. The antioxidant activities of the extracts were evaluated using assays to assess DPPH (1,1-diphenyl-2-picryl-hydrazyl) and hydroxyl radical scavenging activities, metal-chelating activity and reducing power of the extracts. The phenolic, flavonol and flavonoid content of the extracts were also determined. All extracts inhibited the formation of crosslinked AGEs and CML in a dose-dependent manner, with MCF being the most potent. The antioxidant activity of MCF was higher than that of MCP, but MCP showed the highest metal-chelating activity. MCF had the highest phenolic and flavonoid contents, whereas MCP had the highest flavonol content. M. charantia has hypoglycaemic effects, but this study shows that M. charantia extracts are also capable of preventing AGE formation in vitro. This activity may be due to the antioxidant properties, particularly the total phenolic content of the extracts. Thus, the use of M. charantia deserves more attention, as it may not only reduce hyperglycaemia but also protect against the build-up of tissue AGEs and reduce oxidative stress in patients with diabetes

Functional visualisation of genes using singular value decomposition

© 2012, Australian Computer Society, Inc. Progress in understanding core pathways and processes of cancer requires thorough analysis of many coding regions of the genome. New insights are hampered due to the lack of tools to make sense of large lists of genes identified using high throughput technology. Data mining, particularly visualisation that finds relationships between genes and the Gene Ontology (GO), has the potential to assist in functional understanding. This paper addresses the question of how well GO annotations can help in functional understanding of genes. We augment genes with associated GO terms and visualise with Singular Value Decomposition (SVD). Meaning of derived components is further interpreted using correlations to GO terms. The results demonstrate that SVD visualisation of GO-augmented genes matches the biological understanding expected in the simulated data and presents understanding of childhood cancer genes that aligns with published results