Rapid and Highly Informative Diagnostic Assay for H5N1 Influenza Viruses

A highly discriminative and information-rich diagnostic assay for H5N1 avian influenza would meet immediate patient care needs and provide valuable information for public health interventions, e.g., tracking of new and more dangerous variants by geographic area as well as avian-to-human or human-to-human transmission. In the present study, we have designed a rapid assay based on multilocus nucleic acid sequencing that focuses on the biologically significant regions of the H5N1 hemagglutinin gene. This allows the prediction of viral strain, clade, receptor binding properties, low- or high-pathogenicity cleavage site and glycosylation status. H5 HA genes were selected from nine known high-pathogenicity avian influenza subtype H5N1 viruses, based on their diversity in biologically significant regions of hemagglutinin and/or their ability to cause infection in humans. We devised a consensus pre-programmed pyrosequencing strategy, which may be used as a faster, more accurate alternative to de novo sequencing. The available data suggest that the assay described here is a reliable, rapid, information-rich and cost-effective approach for definitive diagnosis of H5N1 avian influenza. Knowledge of the predicted functional sequences of the HA will enhance H5N1 avian influenza surveillance efforts

Leadership and Path Characteristics during Walks Are Linked to Dominance Order and Individual Traits in Dogs

Movement interactions and the underlying social structure in groups have relevance across many social-living species. Collective motion of groups could be based on an “egalitarian” decision system, but in practice it is often influenced by underlying social network structures and by individual characteristics. We investigated whether dominance rank and personality traits are linked to leader and follower roles during joint motion of family dogs. We obtained high-resolution spatio-temporal GPS trajectory data (823,148 data points) from six dogs belonging to the same household and their owner during 14 30–40 min unleashed walks. We identified several features of the dogs' paths (e.g., running speed or distance from the owner) which are characteristic of a given dog. A directional correlation analysis quantifies interactions between pairs of dogs that run loops jointly. We found that dogs play the role of the leader about 50–85% of the time, i.e. the leader and follower roles in a given pair are dynamically interchangable. However, on a longer timescale tendencies to lead differ consistently. The network constructed from these loose leader–follower relations is hierarchical, and the dogs' positions in the network correlates with the age, dominance rank, trainability, controllability, and aggression measures derived from personality questionnaires. We demonstrated the possibility of determining dominance rank and personality traits of an individual based only on its logged movement data. The collective motion of dogs is influenced by underlying social network structures and by characteristics such as personality differences. Our findings could pave the way for automated animal personality and human social interaction measurements

Drug Off-Target Effects Predicted Using Structural Analysis in the Context of a Metabolic Network Model

Recent advances in structural bioinformatics have enabled the prediction of protein-drug off-targets based on their ligand binding sites. Concurrent developments in systems biology allow for prediction of the functional effects of system perturbations using large-scale network models. Integration of these two capabilities provides a framework for evaluating metabolic drug response phenotypes in silico. This combined approach was applied to investigate the hypertensive side effect of the cholesteryl ester transfer protein inhibitor torcetrapib in the context of human renal function. A metabolic kidney model was generated in which to simulate drug treatment. Causal drug off-targets were predicted that have previously been observed to impact renal function in gene-deficient patients and may play a role in the adverse side effects observed in clinical trials. Genetic risk factors for drug treatment were also predicted that correspond to both characterized and unknown renal metabolic disorders as well as cryptic genetic deficiencies that are not expected to exhibit a renal disorder phenotype except under drug treatment. This study represents a novel integration of structural and systems biology and a first step towards computational systems medicine. The methodology introduced herein has important implications for drug development and personalized medicine

Genomic analysis of family data reveals additional genetic effects on intelligence and personality

BioRXiv version. Please see https://rubenarslan.github.io/generation_scotland_pedigree_gcta/ to access this website in a browsable form

Методология синтеза архитектуры программно-технического комплекса автоматизированной системы мониторинга обстановки

Предложен подход к проектированию архитектуры программно-технического комплекса автоматизированной системы мониторинга обстановки в реальном времени, основанный на классификации решаемых функциональных задач на основе методов кластерного анализа и выбранного множества признаков подобия. Разработанный подход позволяет из множества функций системы выделить подобные (по определенным признакам) и объединить их в архитектурные компоненты (унифицированные функциональные модули).Запропоновано підхід до проектування архітектури центру обробки інформації автоматизованої системи моніторингу середовища в реальному часі, що заснований на класифікації функціональних задач на підставі методів кластерного аналізу і обраної множини ознак схожості. Розроблений підхід дозволяє вибрати із множини функцій системи схожі (за певними ознаками) і поєднати їх в архітектурні компоненти (уніфіковані функціональні модулі).The approach to designing architecture of the information processing complex of the automated real time conditions monitoring system based on classification of functional tasks on the basis of methods of cluster analysis and the chosen set of similarity attributes is offered. The developed approach allows to allocate from a set of functions the systems similar (on certain attributes) and to unite them in architectural components (unified functional modules)

Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe