Reconstructing networks of pathways via significance analysis of their intersections

<p>Abstract</p> <p>Background</p> <p>Significance analysis at single gene level may suffer from the limited number of samples and experimental noise that can severely limit the power of the chosen statistical test. This problem is typically approached by applying post hoc corrections to control the false discovery rate, without taking into account prior biological knowledge. Pathway or gene ontology analysis can provide an alternative way to relax the significance threshold applied to single genes and may lead to a better biological interpretation.</p> <p>Results</p> <p>Here we propose a new analysis method based on the study of networks of pathways. These networks are reconstructed considering both the significance of single pathways (network nodes) and the intersection between them (links).</p> <p>We apply this method for the reconstruction of networks of pathways to two gene expression datasets: the first one obtained from a c-Myc rat fibroblast cell line expressing a conditional Myc-estrogen receptor oncoprotein; the second one obtained from the comparison of Acute Myeloid Leukemia and Acute Lymphoblastic Leukemia derived from bone marrow samples.</p> <p>Conclusion</p> <p>Our method extends statistical models that have been recently adopted for the significance analysis of functional groups of genes to infer links between these groups. We show that groups of genes at the interface between different pathways can be considered as relevant even if the pathways they belong to are not significant by themselves.</p

Redescription Mining and Applications in Bioinformatics

Our ability to interrogate the cell and computationally assimilate its answers is improving at a dramatic pace. For instance, the study of even a focused aspect of cellular activity, such as gene action, now benefits from multiple high-throughput data acquisition technologies such as microarrays, genome-wide deletion screens, and RNAi assays. A critical need is the development of algorithms that can bridge, relate, and unify diverse categories of data descriptors. Redescription mining is such an approach. Given a set of biological objects (e.g., genes, proteins) and a collection of descriptors defined over this set, the goal of redescription mining is to use the given descriptors as a vocabulary and find subsets of data that afford multiple definitions. The premise of redescription mining is that subsets that afford multiple definitions are likely to exhibit concerted behavior and are, hence, interesting. We present algorithms for redescription mining based on formal concept analysis and applications of redescription mining to multiple biological datasets. We demonstrate how redescriptions identify conceptual clusters of data using mutually reinforcing features, without explicit training information.

A Semantic Web for bioinformatics: goals, tools, systems, applications

The quantity of biological information is increasing at an impressive rate. An integrated access to this huge amount of information requires complex search and retrieval software and automation of analysis processes. Automation of integration procedures mainly concerns how to link data, how to select and extract information and how to pipe retrieval and analysis steps. This automated approach to data analysis requires the adoption of new technologies and tools in the bioinformatics domain

Precarity and Agency through a Migration Lens

This special issue leverages the migrant experience to better understand precarity and agency in the contemporary world. By way of introduction, we examine the broader bodies of literature on precarity and agency, relate them to research on migration, and link them to the contributions in the special issue. Laying a foundation for further research, we illuminate three approaches to study the precarity-migration-agency nexus: an industry-specific approach, a sending country/deportee approach, and a collective action approach. We conclude with a critical analysis of freedom and national borders, considering the \u27open borders\u27 movement, postnational citizenship, and opposition to marketization