The Molecular Landscape of Premature Aging Diseases Defined by Multilayer Network Exploration.

Premature Aging (PA) diseases are rare genetic disorders that mimic some aspects of physiological aging at an early age. Various causative genes of PA diseases have been identified in recent years, providing insights into some dysfunctional cellular processes. However, the identification of PA genes also revealed significant genetic heterogeneity and highlighted the gaps in this understanding of PA-associated molecular mechanisms.

Random walk with restart on multilayer networks: from node prioritisation to supervised link prediction and beyond.

Background: Biological networks have proven invaluable ability for representing biological knowledge. Multilayer networks, which gather different types of nodes and edges in multiplex, heterogeneous and bipartite networks, provide a natural way to integrate diverse and multi-scale data sources into a common framework. Recently, we developed MultiXrank, a Random Walk with Restart algorithm able to explore such multilayer networks.

N-3 PUFA deficiency disrupts oligodendrocyte maturation and myelin integrity during brain development.

Westernization of dietary habits has led to a progressive reduction in dietary intake of n-3 polyunsaturated fatty acids (n-3 PUFAs). Low maternal intake of n-3 PUFAs has been linked to neurodevelopmental disorders, conditions in which myelination processes are abnormal, leading to defects in brain functional connectivity. Only little is known about the role of n-3 PUFAs in oligodendrocyte physiology and white matter development.

Consensus clustering applied to multi-omics disease subtyping.

Background: Facing the diversity of omics data and the difficulty of selecting one result over all those produced by several methods, consensus strategies have the potential to reconcile multiple inputs and to produce robust results.

Results: Here, we introduce ClustOmics, a generic consensus clustering tool that we use in the context of cancer subtyping. ClustOmics relies on a non-relational graph database, which allows for the simultaneous integration of both multiple omics data and results from various clustering methods.

MoonDB 2.0: an updated database of extreme multifunctional and moonlighting proteins.

MoonDB 2.0 (http://moondb.hb.