Editorial: Repetitive Structures in Biological Sequences: Algorithms and Applications

Repetitive structures in biological sequences are emerging as an active focus of research and the unifying concept of ?repeatome? (the ensemble of knowledge associated with repeating structures in genomic/proteomic data) has been recently proposed in order to highlight several converging trends

Parametric Representation of the Architectural Orders: Testing of Parametric Modelling for Simulation and Interpretation of Classical Architecture

The Architectural Orders have always occupied a key role in architectural doctrine. During the Renaissance, after the rediscovery of the Vitruvian text, each of the most famous architects gave their own interpretation of composition and proportion with respect to the Orders. After a careful analysis of some of the main treaties, it has been necessary to determine a unified interpretation of the genesis of the Orders and to create a single digital model that could be declinable in various versions. By advanced digital techniques, it was possible to generate a representative algorithm in a basic modifiable structure using different parameters. Results are also important due to the direct comparison between authors. The algorithms may also support accurate representations and interpretation of the actual artefact’s shape, allowing us to hypothesize the author’s style and, in case of restoration, to operate in a consistent way

Acute respiratory distress syndrome in an uromastyx (uromastyx acanthinura nigriventris, 1820)

This article describes a case of acute respiratory distress syndrome (ARDS) in a 3-year-old Uromastyx acanthinura gravinensis. The lizard was presented to the veterinary hospital with an 8-day history of respiratory distress. After the initial physical examination, the patient was treated for the respiratory condition for three weeks and subsequently discharged. The bearded dragon died two weeks following release from the veterinary hospital, after an episode of acute dyspnea. Acute respiratory syndrome was diagnosed following histological examination of submitted tissue samples. The authors believe the condition was caused by possible environmental exposure to volatile organic compounds

Discovering chimeric transcripts in paired-end RNA-seq data by using EricScript

Abstract Motivation: The discovery of novel gene fusions can lead to a better comprehension of cancer progression and development. The emergence of deep sequencing of trancriptome, known as RNA-seq, has opened many opportunities for the identification of this class of genomic alterations, leading to the discovery of novel chimeric transcripts in melanomas, breast cancers and lymphomas. Nowadays, few computational approaches have been developed for the detection of chimeric transcripts. Although all of these computational methods show good sensitivity, much work remains to reduce the huge number of false-positive calls that arises from this analysis. Results: We proposed a novel computational framework, named chimEric tranScript detection algorithm (EricScript), for the identification of gene fusion products in paired-end RNA-seq data. Our simulation study on synthetic data demonstrates that EricScript enables to achieve higher sensitivity and specificity than existing methods with noticeably lower running times. We also applied our method to publicly available RNA-seq tumour datasets, and we showed its capability in rediscovering known gene fusions. Availability: The EricScript package is freely available under GPL v3 license at http://ericscript.sourceforge.net. Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics online

Enhanced copy number variants detection from whole-exome sequencing data using EXCAVATOR2

Copy Number Variants (CNVs) are structural rear- rangements contributing to phenotypic variation that have been proved to be associated with many dis- ease states. Over the last years, the identification of CNVs from whole-exome sequencing (WES) data has become a common practice for research and clinical purpose and, consequently, the demand for more and more efficient and accurate methods has increased. In this paper, we demonstrate that more than 30% of WES data map outside the targeted re- gions and that these reads, usually discarded, can be exploited to enhance the identification of CNVs from WES experiments. Here, we present EXCAVATOR2, the first read count based tool that exploits all the reads produced by WES experiments to detect CNVs with a genome-wide resolution. To evaluate the per- formance of our novel tool we use it for analysing two WES data sets, a population data set sequenced by the 1000 Genomes Project and a tumor data set made of bladder cancer samples. The results obtained from these analyses demonstrate that EXCAVATOR2 out- performs other four state-of-the-art methods and that our combined approach enlarge the spectrum of detectable CNVs from WES data with an unprece- dented resolution

Understanding the Pathogenesis of Red Mark Syndrome in Rainbow Trout (Oncorhynchus mykiss) through an Integrated Morphological and Molecular Approach

Red mark syndrome is a non-lethal widespread skin disease mainly reported in rainbow trout and caused by a Midichloria-like organism. Despite extensive research, its etiology and pathogenesis are still uncertain. In the present study, the authors used an integrated morphological and molecular approach, including gene expression, to elucidate the immune response and the complex immune interaction between the host and Midichloria-like organism. The results lead to the conclusions that the most severe skin lesions were characterized by a high level of inflammatory cytokines sustaining and modulating the severe inflammatory process. In contrast, in the moderate form, the response was driven to produce immunoglobulins and IL-10 to control the severity of the disease. Humoral immunity elicited during MLO infection appeared to have a fundamental role in controlling the severity of the skin disease, possibly through bactericidal antibody-mediated mechanisms

Charting differentially methylated regions in cancer with Rocker-meth

Matteo Benelli et al. present Rocker-meth, a new Hidden Markov Model (HMM)-based method, to robustly identify differentially methylated regions (DMRs). They use Rocker-meth to analyse more than 6000 methylation profiles across 14 cancer types, providing a catalog of tumor-specific and shared DMRs

EX-HOM (EXome HOMozygosity): A Proof of Principle

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