The interplay between microscopic and mesoscopic structures in complex networks

Understanding a complex network's structure holds the key to understanding its function. The physics community has contributed a multitude of methods and analyses to this cross-disciplinary endeavor. Structural features exist on both the microscopic level, resulting from differences between single node properties, and the mesoscopic level resulting from properties shared by groups of nodes. Disentangling the determinants of network structure on these different scales has remained a major, and so far unsolved, challenge. Here we show how multiscale generative probabilistic exponential random graph models combined with efficient, distributive message-passing inference techniques can be used to achieve this separation of scales, leading to improved detection accuracy of latent classes as demonstrated on benchmark problems. It sheds new light on the statistical significance of motif-distributions in neural networks and improves the link-prediction accuracy as exemplified for gene-disease associations in the highly consequential Online Mendelian Inheritance in Man database. © 2011 Reichardt et al.

Genetics of ocular disease Part 1: Basic concepts: cells, chromosomes and inheritance

This series of articles describes the basic elements of genetics necessary to understand the new advances and the impact these advances will have on the study and treatment of ocular disease. The first article describes the patterns of inheritance of human characteristics, how they are transmitted between the generations and the structure of chromosomes.

Genetics of ocular disease Part 3: Patterns of inheritance of ocular disease

The objective of this article is to describe the patterns of inheritance exhibited in the human populations and to illustrate them with examples drawn from a variety of ocular diseases.