ArrayMining: a modular web-application for microarray analysis combining ensemble and consensus methods with cross-study normalization

Background: Statistical analysis of DNA microarray data provides a valuable diagnostic tool for the investigation of genetic components of diseases. To take advantage of the multitude of available data sets and analysis methods, it is desirable to combine both different algorithms and data from different studies. Applying ensemble learning, consensus clustering and cross-study normalization methods for this purpose in an almost fully automated process and linking different analysis modules together under a single interface would simplify many microarray analysis tasks. Results: We present ArrayMining.net, a web-application for microarray analysis that provides easy access to a wide choice of feature selection, clustering, prediction, gene set analysis and cross-study normalization methods. In contrast to other microarray-related web-tools, multiple algorithms and data sets for an analysis task can be combined using ensemble feature selection, ensemble prediction, consensus clustering and cross-platform data integration. By interlinking different analysis tools in a modular fashion, new exploratory routes become available, e.g. ensemble sample classification using features obtained from a gene set analysis and data from multiple studies. The analysis is further simplified by automatic parameter selection mechanisms and linkage to web tools and databases for functional annotation and literature mining. Conclusion: ArrayMining.net is a free web-application for microarray analysis combining a broad choice of algorithms based on ensemble and consensus methods, using automatic parameter selection and integration with annotation databases.

Beyond the human genome: microbes, metaphors and what it means to be human in an interconnected post-genomic world

Four years after the completion of the Human Genome Project, the US National Institutes for Health launched the Human Microbiome Project on 19 December 2007. Using metaphor analysis, this article investigates reporting in English-language newspapers on advances in microbiomics from 2003 onwards, when the word “microbiome” was first used. This research was said to open up a “new frontier” and was conceived as a “second human genome project”, this time focusing on the genomes of microbes that inhabit and populate humans rather than focusing on the human genome itself. The language used by scientists and by the journalists who reported on their research employed a type of metaphorical framing that was very different from the hyperbole surrounding the decipherment of the “book of life”. Whereas during the HGP genomic successes had been mainly framed as being based on a unidirectional process of reading off information from a passive genetic or genomic entity, the language employed to discuss advances in microbiomics frames genes, genomes and life in much more active and dynamic ways.