2 results for Affara, M

  • Gene network inference and visualization tools for biologists: application to new human transcriptome datasets.

    Hurley, Daniel; Araki, Hiromitsu; Tamada, Y; Dunmore, B; Sanders, D; Humphreys, S; Affara, M; Imoto, S; Yasuda, K; Tomiyasu, Y; Tashiro, K; Savoie, C; Cho, V; Smith, S; Kuhara, S; Miyano, S; Charnock-Jones, DS; Crampin, Edmund; Print, Cristin (2012)

    Journal article
    The University of Auckland Library

    Gene regulatory networks inferred from RNA abundance data have generated significant interest, but despite this, gene network approaches are used infrequently and often require input from bioinformaticians. We have assembled a suite of tools for analysing regulatory networks, and we illustrate their use with microarray datasets generated in human endothelial cells. We infer a range of regulatory networks, and based on this analysis discuss the strengths and limitations of network inference from RNA abundance data. We welcome contact from researchers interested in using our inference and visualization tools to answer biological questions.

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  • Understanding Endothelial Cell Apoptosis: What can the transcriptome glycome and proteome reveal?

    Affara, M; Dunmore, B; Savoie, C; Charnock-Jones, S; Print, Cristin (2007)

    Journal article
    The University of Auckland Library

    Endothelial cell (EC) apoptosis may play an important role in blood vessel development, homeostasis and remodelling. In support of this concept, EC apoptosis has been detected within remodelling vessels in vivo, and inactivation of EC apoptosis regulators has caused dramatic vascular phenotypes. EC apoptosis has also been associated with cardiovascular pathologies. Therefore, understanding the regulation of EC apoptosis, with the goal of intervening in this process, has become a current research focus. The protein-based signalling and cleavage cascades that regulate EC apoptosis are well known. However, the possibility that programmed transcriptome and glycome changes contribute to EC apoptosis has only recently been explored. Traditional bioinformatic techniques have allowed simultaneous study of thousands of molecular signals during the process of EC apoptosis. However, to progress further, we now need to understand the complex cause and effect relationships among these signals. In this article, we will ???rst review current knowledge about the function and regulation of EC apoptosis including the roles of the proteome transcriptome and glycome. Then, we assess the potential for further bioinformatic analysis to advance our understanding of EC apoptosis, including the limitations of current technologies and the potential of emerging technologies such as gene regulatory networks.

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