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Title: | Bioinformatics tools in predictive ecology: Applications to fisheries |
Authors: | Tucker, A Duplisea, D |
Keywords: | Bioinformatics;Bayesian networks;Classification;Dynamic models;Fisheries management |
Issue Date: | 2012 |
Publisher: | Royal Society Publishing |
Citation: | Philosophical Transactions of the Royal Society: Part B, 367: 279 - 290, Jan 2012 |
Abstract: | There has been a huge effort in the advancement of analytical techniques for molecular biological data over the past decade. This has led to many novel algorithms that are specialized to deal with data associated with biological phenomena, such as gene expression and protein interactions. In contrast, ecological data analysis has remained focused to some degree on off-the-shelf statistical techniques though this is starting to change with the adoption of state-of-the-art methods, where few assumptions can be made about the data and a more explorative approach is required, for example, through the use of Bayesian networks. In this paper, some novel bioinformatics tools for microarray data are discussed along with their ‘crossover potential’ with an application to fisheries data. In particular, a focus is made on the development of models that identify functionally equivalent species in different fish communities with the aim of predicting functional collapse. |
Description: | This article is made available throught the Brunel Open Access Publishing Fund - Copygith @ 2012 Tucker et al. |
URI: | http://rstb.royalsocietypublishing.org/content/367/1586/279.abstract http://bura.brunel.ac.uk/handle/2438/6141 |
DOI: | http://dx.doi.org/10.1098/rstb.2011.0184 |
ISSN: | 0962-8436 |
Appears in Collections: | Computer Science Brunel OA Publishing Fund Dept of Computer Science Research Papers |
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