Fast Comparison of Microbial Genomes Using the Chaos Games Representation for Metagenomic Applications

AbstractGenome sequencing technology is generating large databases of sequence at such a rate that advances in computer hardware alone are not adequate to handle them: more efficient algorithms are needed. Here an alignment-free method of sequence comparison and visualisation based on the Chaos Games Representation (CGR) and multifractal analysis is explored as an approach to search and filter through a data set of over 1500 microbial genomes. Whereas BLAST takes 25hours to search this data set with large sequence fragments (e.g. 100 Kb), the method introduced here can reduce this data set by 95% (from 1550 target species to just 50) in about 15minutes, and it is able to predict the exact species correctly in 67% of cases. The results presented here demonstrate that CGR is worth further investigation as a fast method to perform genome sequence comparison on large data sets, and various ways to further develop the method are discussed

The solubilization of mitochondrial protein by nonionic surface active agents

LD2668 .T4 1966 S971Master of Scienc

Tragic but brave or just crips with chips? Songs and their lyrics in the Disability Arts Movement in Britain

Disability culture is a site within which social and positional identities are struggled for and dominant discourses rejected; in which mainstream representations of people with impairments – as victims of personal tragedy – are held to the light and revealed as hegemonic constructions within a disabling society. Drawing upon styles that range from jazz, blues and folk to reggae, performance poetry and punk, disabled singers and bands in the Disability Arts Movement in Britain have been central to the development of an affirmative disability discourse rooted in ideas of pride, anger and strength. Examining lyrics by Johnny Crescendo, Ian Stanton and the Fugertivs – performers emerging as part of this movement in the 1980s and 1990s – this article considers the dark humour which runs through much of this work. It is suggested that these lyrics' observational reflections on everyday experiences of being oppressed as disabled people have been overlooked within critical disability studies to date, but are important in developing an understanding of positive disability identity as a tool available to disabled people in order to make sense of, and express themselves within, the world in which they find themselves

Brca2 and Trp53 deficiency cooperate in the progression of mouse prostate tumourigenesis.

Epidemiological studies have shown that one of the strongest risk factors for prostate cancer is a family history of the disease, suggesting that inherited factors play a major role in prostate cancer susceptibility. Germline mutations in BRCA2 predispose to breast and ovarian cancer with its predominant tumour suppressor function thought to be the repair of DNA double-strand breaks. BRCA2 has also been implicated in prostate cancer etiology, but it is unclear the impact that mutations in this gene have on prostate tumourigenesis. Here we have undertaken a genetic analysis in the mouse to determine the role of Brca2 in the adult prostate. We show that deletion of Brca2 specifically in prostate epithelia results in focal hyperplasia and low-grade prostate intraepithelial neoplasia (PIN) in animals over 12 months of age. Simultaneous deletion of Brca2 and the tumour suppressor Trp53 in prostate epithelia gave rise to focal hyperplasia and atypical cells at 6 months, leading to high-grade PIN in animals from 12 months. Epithelial cells in these lesions show an increase in DNA damage and have higher levels of proliferation, but also elevated apoptosis. Castration of Brca2;Trp53 mutant animals led to regression of PIN lesions, but atypical cells persisted that continued to proliferate and express nuclear androgen receptor. This study provides evidence that Brca2 can act as a tumour suppressor in the prostate, and the model we describe should prove useful in the development of new therapeutic approaches

Homogeneous and heterogeneous populations of active rods in two-dimensional channels

Active swarms, consisting of individual agents which consume energy to move or produce work, are known to generate a diverse range of collective behaviors. Many examples of active swarms are biological in nature (e.g., fish shoals and bird flocks) and have been modeled extensively by numerical simulations. Such simulations of swarms usually assume that the swarm is homogeneous; that is, every agent has exactly the same dynamical properties. However, many biological swarms are highly heterogeneous, such as multispecies communities of micro-organisms in soil, and individual species may have a wide range of different physical properties. Here we explore heterogeneity by developing a simple model for the dynamics of a swarm of motile heterogeneous rodlike bacteria in the absence of hydrodynamic effects. Using molecular dynamics simulations of active rods confined within a two-dimensional rectangular channel, we first explore the case of homogeneous swarms and show that the key parameter governing both dynamics is ratio of the motility force to the steric force. Next we explore heterogeneous or mixed swarms in which the constituent self-propelled rods have a range of motilities and steric interactions. Our results show that the confining boundaries play a strong role in driving the segregation of mixed populations.Comment: 9 pages, 10 figure

Comparative study of three commonly used continuous deterministic methods for modeling gene regulation networks

BACKGROUND: A gene-regulatory network (GRN) refers to DNA segments that interact through their RNA and protein products and thereby govern the rates at which genes are transcribed. Creating accurate dynamic models of GRNs is gaining importance in biomedical research and development. To improve our understanding of continuous deterministic modeling methods employed to construct dynamic GRN models, we have carried out a comprehensive comparative study of three commonly used systems of ordinary differential equations: The S-system (SS), artificial neural networks (ANNs), and the general rate law of transcription (GRLOT) method. These were thoroughly evaluated in terms of their ability to replicate the reference models' regulatory structure and dynamic gene expression behavior under varying conditions. RESULTS: While the ANN and GRLOT methods appeared to produce robust models even when the model parameters deviated considerably from those of the reference models, SS-based models exhibited a notable loss of performance even when the parameters of the reverse-engineered models corresponded closely to those of the reference models: this is due to the high number of power terms in the SS-method, and the manner in which they are combined. In cross-method reverse-engineering experiments the different characteristics, biases and idiosynchracies of the methods were revealed. Based on limited training data, with only one experimental condition, all methods produced dynamic models that were able to reproduce the training data accurately. However, an accurate reproduction of regulatory network features was only possible with training data originating from multiple experiments under varying conditions. CONCLUSIONS: The studied GRN modeling methods produced dynamic GRN models exhibiting marked differences in their ability to replicate the reference models' structure and behavior. Our results suggest that care should be taking when a method is chosen for a particular application. In particular, reliance on only a single method might unduly bias the results

MetaPred2CS:A sequence-based meta-predictor for protein-protein interactions of prokaryotic two-component system proteins

Abstract Motivation: Two-component systems (TCS) are the main signalling pathways of prokaryotes, and control a wide range of biological phenomena. Their functioning depends on interactions between TCS proteins, the specificity of which is poorly understood. Results: The MetaPred2CS web-server interfaces a sequence-based meta-predictor specifically designed to predict pairing of the histidine kinase and response-regulator proteins forming TCSs. MetaPred2CS integrates six sequence-based methods using a support vector machine classifier and has been intensively tested under different benchmarking conditions: (i) species specific gene sets; (ii) neighbouring versus orphan pairs; and (iii) k-fold cross validation on experimentally validated datasets. Availability and Implementation: Web server at: http://metapred2cs.ibers.aber.ac.uk/ , Source code: https://github.com/martinjvickers/MetaPred2CS or implemented as Virtual Machine at: http://metapred2cs.ibers.aber.ac.uk/download Contact:  [email protected] Supplementary information:  Supplementary data are available at Bioinformatics online.</jats:p

Changing classroom practice in science and mathematics lessons in Egypt : inhibitors and opportunities

Egyptian science and mathematics teachers self-report shows that examinations are viewed as the dominant factor inhibiting changes to classroom practice. Although future reforms need to be focused on examinations, the analysis presented here suggests such work needs to be accompanied by changes to textbooks and classroom resources. As inhibitors to change are also located in students and their parents another task is helping them to reconsider what counts as education. The evidence comes from a postal survey of Egyptian science and mathematics teachers following their twelve week in-service programmes in the UK.peer-reviewe

G-Anchor:A novel approach for whole-genome comparative mapping utilising evolutionary conserved DNA sequences

Background Cross-species whole-genome sequence alignment is a critical first step for genome comparative analyses ranging from the detection of sequence variants to studies of chromosome evolution. Animal genomes are large and complex, and whole-genome alignment is a computationally intense process, requiring expensive high performance computing systems due to the need to explore extensive local alignments. With hundreds of sequenced animal genomes available now from multiple projects there is an increasing demand for genome comparative analyses. Results Here we introduce G-Anchor, a new, fast, and efficient pipeline that uses a strictly limited but highly effective set of local sequence alignments to anchor (or map) an animal genome to another species? reference genome. G-Anchor makes novel use of a databank of highly conserved DNA sequence elements. We demonstrate how these elements may be aligned to a pair of genomes, creating anchors. These anchors enable the rapid mapping of scaffolds from a de novo assembled genome to chromosome assemblies of a reference species. Our results demonstrate that G-Anchor can successfully anchor a vertebrate genome onto a phylogenetically related reference species genome using a desktop or laptop computer within a few hours, and with comparable accuracy to that achieved by a highly accurate whole-genome alignment tool such as LASTZ. G-Anchor thus makes whole-genome comparisons accessible to researchers with limited computational resources. Conclusions G-Anchor is a ready-to-use tool for anchoring a pair of vertebrate genomes. It may be used with large genomes that contain a significant fraction of evolutionally conserved DNA sequences, and that are not highly repetitive, polypoid or excessively fragmented. G-Anchor is not a substitute for whole-genome aligning software but can be used for fast and accurate initial genome comparisons. G-Anchor is freely available via https://github.com/vasilislenis/G-AnchorpublishersversionPeer reviewe