CINECA IRIS Institutional Research Information System

IRIS è la soluzione IT che facilita la raccolta e la gestione dei dati relativi alle attività e ai prodotti della ricerca. Fornisce a ricercatori, amministratori e valutatori gli strumenti per monitorare i risultati della ricerca, aumentarne la visibilità e allocare in modo efficace le risorse disponibili.

Prodotti recenti

Vertebrate Genome Size and the Impact of Transposable Elements in Genome Evolution

In eukaryotes, the haploid DNA content (C-value) varies widely across lineages without an apparent correlation with the complexity of organisms. This incongruity has been called the C-value paradox and has been solved by demonstrating that not all DNA is constituted by genes but, o...

Structural determinants of CO2-sensitivity in the β connexin family suggested by evolutionary analysis

A subclade of connexins comprising Cx26, Cx30, and Cx32 are directly sensitive to CO2. CO2 binds to a carbamylation motif present in these connexins and causes their hemichannels to open. Cx26 may contribute to CO2-dependent regulation of breathing in mammals. Here, we show that&#x...

Mitochondrial impairment activates the Wallerian pathway through depletion of NMNAT2 leading to SARM1-dependent axon degeneration

Wallerian degeneration of physically injured axons involves a well-defined molecular pathway linking loss of axonal survival factor NMNAT2 to activation of pro-degenerative protein SARM1. Manipulating the pathway through these proteins led to the identification of non-axotomy insults causing axon dege...

An intriguing relationship between teleost Rex3 retroelement and environmental temperature

The movement and accumulation of transposable elements (TEs) exert a great influence on the host genome, e.g. determining architecture and genome size, providing a substrate for homologous recombination and DNA rearrangements. TEs are also known to be responsive and susceptible to environmen...

A Machine Learning Approach to the Identification of Dynamical Nonlinear Systems

The aim of this paper is to present a general machine learning approach to the identification of nonlinear systems, using the observed input-output finite datasets. The approach is derived representing the input and output signals in the feature space by the principal component ana...