ArticlePhilosophical transactions of the Royal Society of London. Series B, Biological sciences2012
Bioinformatics tools in predictive ecology: applications to fisheries.
Article in Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- Uncovering ecological state dynamics with hidden Markov models.Ecology letters · 2020Review
- Predictive ecology: systems approaches.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2012Article
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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