Influence of homology and node-age on the growth of protein-protein interaction networks

Proteins participating in a protein-protein interaction network can be grouped into homology classes following their common ancestry. Proteins added to the network correspond to genes added to the classes, so that the dynamics of the two objects are intrinsically linked. Here, we first introduce a statistical model describing the joint growth of the network and the partitioning of nodes into classes, which is studied through a combined mean-field and simulation approach. We then employ this unified framework to address the specific issue of the age dependence of protein interactions, through the definition of three different node wiring/divergence schemes. Comparison with empirical data indicates that an age-dependent divergence move is necessary in order to reproduce the basic topological observables together with the age correlation between interacting nodes visible in empirical data. We also discuss the possibility of nontrivial joint partition/topology observables.Comment: 14 pages, 7 figures [accepted for publication in PRE

Superconductivity in doped sp3 semiconductors: The case of the clathrates

We present a joint experimental and theoretical study of the superconductivity in doped silicon clathrates. The critical temperature in Ba-8@Si-46 is shown to strongly decrease with applied pressure. These results are corroborated by ab initio calculations using MacMillan's formulation of the BCS theory with the electron-phonon coupling constant lambda calculated from perturbative density functional theory. Further, the study of I-8@Si-46 and of gedanken pure silicon diamond and clathrate phases doped within a rigid-band approach show that the superconductivity is an intrinsic property of the sp(3) silicon network. As a consequence, carbon clathrates are predicted to yield large critical temperatures with an effective electron-phonon interaction much larger than in C-60

Epidemiology, Diagnosis, and Management of Cystic Lesions of the Pancreas

Although little is known on the true prevalence of pancreatic cysts, physicians are currently more frequently confronted with pancreatic cysts because of the increasing use of sophisticated cross-sectional abdominal imaging. Cystic lesions of the pancreas comprise of a heterogeneous group of diagnostic entities, some of which are benign such as inflammatory pseudocysts or serous cystadenomas and do not require resection when asymptomatic. Others like mucinous cysts or intraductal papillary mucinous neoplasms (IPMN) have a malignant potential and in these cases surgical resection is often indicated. For this reason an adequate distinction between the various cysts is crucial to optimize management strategy. Different diagnostic methods that could be of value in the differentiation include radiologic imaging techniques such as CT, MR, and endosonography. In addition, fluid aspiration for cytopathology, tumormarkers or molecular analysis is widely used. Different guidelines are available but so far no optimal diagnostic algorithm exists. We summarize the epidemiology, classification, clinical presentation, diagnostics, management, and future perspectives

Statistical Mechanics of the Chinese Restaurant Process: lack of self-averaging, anomalous finite-size effects and condensation

The Pitman-Yor, or Chinese Restaurant Process, is a stochastic process that generates distributions following a power-law with exponents lower than two, as found in a numerous physical, biological, technological and social systems. We discuss its rich behavior with the tools and viewpoint of statistical mechanics. We show that this process invariably gives rise to a condensation, i.e. a distribution dominated by a finite number of classes. We also evaluate thoroughly the finite-size effects, finding that the lack of stationary state and self-averaging of the process creates realization-dependent cutoffs and behavior of the distributions with no equivalent in other statistical mechanical models.Comment: (5pages, 1 figure

Science Reproducibility and Reusability with FutureGateway and a Zenodo-like repository: the PALMS experiment

Open Science (OS) is a powerful and novel paradigm to share knowledge across multidisciplinary scientific communities with the aim to improve the quality of science. One of the most important OS enablers are the FAIR principles, which involves the way to Find, Access, Interoperate and Reuse research data. In most of the cases published scholarship materials are not linked with computed datasets, open source software and/or virtualized computing environments and OS currently lacks of means helping to reproduce and eventually reuse cited results exploiting public or private distributed computing infrastructures (DCIs). Moreover, from the final user point of view, the best option would be the use of graphical user interfaces (GUIs) normally hosted by a Science Gateway (SG) built for a specific scientific community. The FutureGateway Framework (FGF) consists of a complete software toolkit made of different parts such as: source codes, utilities, libraries and APIs capable to comfortably build reliable Science Gateways and link them to one or more DCIs avoiding any usage complexity from the final user perspective. Moreover, since SGs based on the FGF are capable to keep track of who is accessing the DCIs, not only its usage ensures OS-compliant reproducibility and reusability but also provides a possible answer in protecting or at least simply tracking people who are accessing data and this is one of the aspects that today still makes the adoption of the OS a delicate matter. This work presents and explains how the use of the EGI's Science Software on Demand (SSOD) service, built using the FutureGatewayFramework in conjunction with the INFN Open Access Repository (OAR), based on Zenodo software, can reproduce/reuse the outputs of the agent-based Physical Activity Lifelong Modelling & Simulations (PALMS) experiment

INSPEcT: a computational tool to infer mRNA synthesis, processing and degradation dynamics from RNA- and 4sU-seq time course experiments.

Abstract Motivation: Cellular mRNA levels originate from the combined action of multiple regulatory processes, which can be recapitulated by the rates of pre-mRNA synthesis, pre-mRNA processing and mRNA degradation. Recent experimental and computational advances set the basis to study these intertwined levels of regulation. Nevertheless, software for the comprehensive quantification of RNA dynamics is still lacking. Results: INSPEcT is an R package for the integrative analysis of RNA- and 4sU-seq data to study the dynamics of transcriptional regulation. INSPEcT provides gene-level quantification of these rates, and a modeling framework to identify which of these regulatory processes are most likely to explain the observed mRNA and pre-mRNA concentrations. Software performance is tested on a synthetic dataset, instrumental to guide the choice of the modeling parameters and the experimental design. Availability and implementation: INSPEcT is submitted to Bioconductor and is currently available as Supplementary Additional File S1. Contact: [email protected] Supplementary Information: Supplementary data are available at Bioinformatics online

Traumatic experiences in a lifetime: impact on the connection with others and the role of emotions

Abstract in proceedings of the Fourth International Congress of CiiEM: Health, Well-Being and Ageing in the 21st Century, held at Egas Moniz’ University Campus in Monte de Caparica, Almada, from 3–5 June 2019.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.info:eu-repo/semantics/publishedVersio

Selective transcriptional regulation by Myc: Experimental design and computational analysis of high-throughput sequencing data

AbstractThe gene expression programs regulated by the Myc transcription factor were evaluated by integrated genome-wide profiling of Myc binding sites, chromatin marks and RNA expression in several biological models. Our results indicate that Myc directly drives selective transcriptional regulation, which in certain physiological conditions may indirectly lead to RNA amplification. Here, we illustrate in detail the experimental design concerning the high-throughput sequencing data associated with our study (Sabò et al., Nature. (2014) 511:488–492) and the R scripts used for their computational analysis