The impact of genome defense on mobile elements in Microbotryum

Repeat induced point mutation (RIP), a mechanism causing hypermutation of repetitive DNA sequences in fungi, has been described as a ‘genome defense’ which functions to inactivate mobile elements and inhibit their deleterious effects on genome stability. Here we address the interactions between RIP and transposable elements in the Microbotryum violaceum species complex. Ten strains of M. violaceum, most of which belong to different species of the fungus, were all found to contain intragenomic populations of copia-like retrotransposons. Intragenomic DNA sequence variation among the copia-like elements was analyzed for evidence of RIP. Among species with RIP, there was no significant correlation between the frequency of RIP-induced mutations and inferred transposition rate based on diversity. Two strains of M. violaceum, from two different plant species but belonging to the same fungal lineage, contained copia-like elements with very low diversity, as would result from a high transposition rate, and these were also unique in showing no evidence of the hypermutation patterns indicative of the RIP genome defense. In this species, evidence of RIP was also absent from a Class II helitron-like transposable element. However, unexpectedly the absolute repetitive element load was lower than in other strains.

A blueprint for affective computing: A sourcebook

A Blueprint for Affective Computing: A sourcebook and manual is the very first attempt to ground affective computing within the disciplines of psychology, affective neuroscience, and philosophy. This book illustrates the contributions of each of these disciplines to the development of the ever-growing field of affective computing. In addition, it demonstrates practical examples of cross-fertilization between disciplines in order to highlight the need for integration of computer science, engineering and the affective sciences.

Cultured neural networks

This article looks at the use of cultured neural networks as the decision-making mechanism of a control system. In this case biological neurons are grown and trained to act as an artificial intelligence engine. Such research has immediate medical implications as well as enormous potential in computing and robotics. An experimental system involving closed-loop control of a mobile robot by a culture of neurons has been successfully created and is described here. This article gives a brief overview of the problem area and ongoing research. Questions are asked as to where this will lead in the future.