301 research outputs found

    Multiobjective Reliable Cloud Storage with Its Particle Swarm Optimization Algorithm

    Get PDF
    Information abounds in all fields of the real life, which is often recorded as digital data in computer systems and treated as a kind of increasingly important resource. Its increasing volume growth causes great difficulties in both storage and analysis. The massive data storage in cloud environments has significant impacts on the quality of service (QoS) of the systems, which is becoming an increasingly challenging problem. In this paper, we propose a multiobjective optimization model for the reliable data storage in clouds through considering both cost and reliability of the storage service simultaneously. In the proposed model, the total cost is analyzed to be composed of storage space occupation cost, data migration cost, and communication cost. According to the analysis of the storage process, the transmission reliability, equipment stability, and software reliability are taken into account in the storage reliability evaluation. To solve the proposed multiobjective model, a Constrained Multiobjective Particle Swarm Optimization (CMPSO) algorithm is designed. At last, experiments are designed to validate the proposed model and its solution PSO algorithm. In the experiments, the proposed model is tested in cooperation with 3 storage strategies. Experimental results show that the proposed model is positive and effective. The experimental results also demonstrate that the proposed model can perform much better in alliance with proper file splitting methods

    Acute Myeloid Leukemia

    Get PDF
    Acute myeloid leukemia (AML) is the most common type of leukemia. The Cancer Genome Atlas Research Network has demonstrated the increasing genomic complexity of acute myeloid leukemia (AML). In addition, the network has facilitated our understanding of the molecular events leading to this deadly form of malignancy for which the prognosis has not improved over past decades. AML is a highly heterogeneous disease, and cytogenetics and molecular analysis of the various chromosome aberrations including deletions, duplications, aneuploidy, balanced reciprocal translocations and fusion of transcription factor genes and tyrosine kinases has led to better understanding and identification of subgroups of AML with different prognoses. Furthermore, molecular classification based on mRNA expression profiling has facilitated identification of novel subclasses and defined high-, poor-risk AML based on specific molecular signatures. However, despite increased understanding of AML genetics, the outcome for AML patients whose number is likely to rise as the population ages, has not changed significantly. Until it does, further investigation of the genomic complexity of the disease and advances in drug development are needed. In this review, leading AML clinicians and research investigators provide an up-to-date understanding of the molecular biology of the disease addressing advances in diagnosis, classification, prognostication and therapeutic strategies that may have significant promise and impact on overall patient survival

    Mechanistic analysis of nonribosomal peptide synthetases

    Get PDF
    Considering the ongoing rise of the multidrug-resistant bacterial infections, it is essential to expand the available repertoire of therapeutic agents. Microbial natural products are an indispensable source of novel activities and continue to serve as our main provider of antibiotics and chemotherapeutics. Nonribosomal peptides are among the most widespread natural products in bacteria and fungi. Their importance is best illustrated by their complexity and the amounts of resources dedicated to building the underlying biosynthetic machineries nonribosomal peptide synthetases (NRPS). These gigantic, multidomain enzymes synthesize peptides by linking individual amino acid units in an assembly line fashion. Six decades of NRPS research have resulted in several remarkable tailoring successes. However, the lack of mechanistic understanding of the inner workings of NRPSs has prevented the development of a general workflow which would reliably generate functional enzymes and new drugs. Aspiring to alleviate these obstacles, this thesis offers critical insights into adenylation and the interplay with condensation, two fundamental NRPS reactions

    Exploring the biosynthetic logic of myxobacterial natural products

    Get PDF
    Myxobacteria produce a wide range of natural products exhibiting intriguing structures and potent biological activities. Natural products are formed by a variety of biosynthetic machineries. The genetic information for those biosynthetic machineries is encoded in the genome of each bacterium. Genome sequencing of myxobacteria has revealed numerous biosynthetic pathways comprised of biosynthetic proteins which to date have not yet been associated with their corresponding natural products. This thesis covers the identification and exploration of the biosynthetic origin of six myxobacterial natural product classes, thereby employing diverse concepts and methods of natural product research. The biosyntheses of natural products were investigated through mass spectrometry and genomics-guided techniques, stable-isotope-labeled feeding experiments combined with in silico analysis, genetic engineering of myxobacteria, biochemical characterization of biosynthetic proteins and structure elucidation of natural products using spectroscopic methods. These efforts expanded the knowledge of myxobacterial natural product biosynthesis and revealed unprecedented biosynthetic pathways.Myxobakterien produzieren eine Vielzahl von Naturstoffen, die beeindruckende Strukturen und potente biologische Aktivitäten aufweisen. Naturstoffe werden von einer Vielzahl von biosynthetischen Maschinerien produziert. Die genetische Information um diese biosynthetischen Maschinerien zu generieren ist in dem Genom des jeweiligen Bakteriums enkodiert. Genomsequenzierungen von Myxobakterien offenbarten zahlreiche biosynthetische Stoffwechselwege, welche aus biosynthetischen Proteinen bestehen und bis heute zu keinen korrespondierenden Naturstoffen zugeordnet werden konnten. Die vorliegende Dissertation umfasst die Identifizierung und Erforschung der biosynthetischen Ursprünge von sechs myxobakteriellen Naturstoffklassen und dementsprechend wurden diverse Konzepte und Methoden der Naturstoffforschung angewandt. Die Biosynthesen von Naturstoffen wurde durch massenspektrometrischen und genomgeleiteten Techniken, stabile isotopenmarkierte Fütterungsexperimenten in Kombination mit in silico Analysen, gentechnischen Manipulationen von Myxobakterien, durch die Charakterisierung von biosynthetischen Proteinen und durch die Strukturaufklärung von Naturstoffen mit Hilfe spektroskopischer Methoden untersucht. Diese Arbeiten haben zur Erweiterung des Wissensstands der myxobakteriellen Naturstoffbiosynthese beigetragen und dabei beispiellose biosynthetische Stoffwechselwege offenbart.Boehringer Ingelheim Fond

    DNA metabarcoding of zooplankton enhances community-level analyses of connectivity in a marine pelagic environment.

    Get PDF
    Doctoral Degree. University of KwaZulu-Natal, Pietermaritzburg.Zooplankton are abundant and diverse marine organisms that form ecologically important communities in marine pelagic ecosystems. They are well-suited for biomonitoring of ecosystem health and changes in biodiversity because their community structure and biomass respond rapidly to environmental variation. Biomonitoring of zooplankton communities using traditional morphology-based species identification methods is labor-intensive due to their cryptic morphology, high diversity and small body size. Fast-developing molecular techniques such as DNA metabarcoding (large-scale, high-throughput DNA sequencing of targeted gene regions to simultaneously identify multiple species present in samples) may provide higher resolution, accurate, faster and more cost-effective biomonitoring tools. The primary objectives of this dissertation were to develop and test a novel DNA metabarcoding approach for biomonitoring of marine zooplankton over the continental shelf of eastern South Africa. Novel taxon-specific DNA mini-barcode primers were designed to increase species identification rates of selected taxa. Artificially assembled mock communities with known composition and relative abundances were then used in an experimental setup to test detection rates and the accuracy of designed and published primers. The DNA metabarcoding protocol was then used to assess connectivity among zooplankton communities over the narrow KwaZulu-Natal continental shelf. Plankton tow nets were used to sample cross-shelf transects at three sites (uThukela, Durban and Aliwal), which are strongly influenced by the Agulhas Current but differ in shelf width, seafloor substrate and benthic habitat structures. Connectivity network analysis detected distinct clustering of zooplankton communities associated with each transect. The hypothesis that a dynamic ocean current regime associated with the offshore Agulhas Current (nearby and flowing parallel to the shelf-edge) would result in similar well-mixed alongshore zooplankton communities was rejected. A strong benthicpelagic coupling effect was inferred based on the species composition of planktonic larvae and benthic adults occurring at the respective transects. This dissertation provides a refined and novel method for biomonitoring of marine pelagic environments in coastal waters, based on taxonspecific DNA metabarcoding of zooplankton communities. The approach is well-suited to measuring the long-term effects of climate change on marine pelagic ecosystems and ocean productivity

    Human Machine Interaction

    Get PDF
    In this book, the reader will find a set of papers divided into two sections. The first section presents different proposals focused on the human-machine interaction development process. The second section is devoted to different aspects of interaction, with a special emphasis on the physical interaction

    Combining automated processing and customized analysis for large-scale sequencing data

    Get PDF
    Extensive application of high-throughput methods in life sciences has brought substantial new challenges for data analysis. Often many different steps have to be applied to a large number of samples. Here, workflow management systems support scientists through the automated execution of corresponding large analysis workflows. The first part of this cumulative dissertation concentrates on the development of Watchdog, a novel workflow management system for the automated analysis of large-scale experimental data. Watchdog`s main features include straightforward processing of replicate data, support for distributed computer systems, customizable error detection and manual intervention into workflow execution. A graphical user interface enables workflow construction using a pre-defined toolset without programming experience and a community sharing platform allows scientists to share toolsets and workflows efficiently. Furthermore, we implemented methods for resuming execution of interrupted or partially modified workflows and for automated deployment of software using package managers and container virtualization. Using Watchdog, we implemented default analysis workflows for typical types of large-scale biological experiments, such as RNA-seq and ChIP-seq. Although they can be easily applied to new datasets of the same type, at some point such standard workflows reach their limit and customized methods are required to resolve specific questions. Hence, the second part of this dissertation focuses on combining standard analysis workflows with the development of application-specific novel bioinformatics approaches to address questions of interest to our biological collaboration partners. The first study concentrates on identifying the binding motif of the ZNF768 transcription factor, which consists of two anchor regions connected by a variable linker region. As standard motif finding methods detected only the anchors of the motifs separately, a custom method was developed for determining the spaced motif with the linker region. The second study focused on the effect of CDK12 inhibition on transcription. Results obtained from standard RNA-seq analysis indicated substantial transcript shortening upon CDK12 inhibition. We thus developed a new measure to quantify the degree of transcript shortening. In addition, a customized meta-gene analysis framework was developed to model RNA polymerase II progression using ChIP-seq data. This revealed that CDK12 inhibition causes an RNA polymerase II processivity defect resulting in the detected transcript shortening. In summary, the methods developed in this thesis represent both general contributions to large-scale sequencing data analysis and served to resolve specific questions regarding transcription factor binding and regulation of elongating RNA Polymerase II

    Metrology and Molecular Diagnosis of Infection

    Get PDF
    Metrology, the study of measurement, is an emerging concept within molecular diagnosis of infection. Metrology promotes high-quality, reproducible data to be used in clinical management of infection, through characterisation of technical error and measurement harmonisation. This influences measurement accuracy, which has implications for setting thresholds between healthy and disease states, monitoring disease progression, and establishing cures. This thesis examines the placing of metrology in molecular diagnosis of infectious diseases. Sources of experimental error in advanced methodologies – dPCR and MALDI-TOF MS – that can influence measurement accuracy for RNA, DNA and protein biomarkers were investigated for HIV-1, methicillin-resistant Staphylococcus spp and organisms associated with hospital transmission. Measurement error introduced at different stages of a method can directly impact upon clinical results. A 30% bias was introduced between dPCR and qPCR quantification of HIV-1 DNA in clinical samples, owing to instability in the qPCR calibration material. In addition, experimental variability was found to influence classification of protein profiles which can limit the resolution of MALDI-TOF MS for strain typing bacteria. This thesis also addresses the prospective role of these advanced methods in supporting accurate clinical measurements. dPCR offers precise measurements of RNA and DNA targets and could be used to support qPCR, or for value assignment of reference materials to harmonise inter-laboratory results. MALDI-TOF MS demonstrated potential for strain typing Acinetobacter baumannii; results correlated with epidemiological data and WGS, although were not consistent with reference typing. Further work should examine the extent to which MALDI-TOF MS can support or replace contemporary strain typing methods for identifying nosocomial outbreaks. Molecular approaches possess a crucial role in the detection, quantification and characterisation of pathogens, and are invaluable tools for managing emerging diseases. Supporting accuracy and reproducibility in molecular measurements could help to strengthen diagnostic efforts, streamline clinical pathways and provide overall benefit to patient care
    • …
    corecore