880 resultados para high-throughput methods


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Information reconciliation is a crucial procedure in the classical post-processing of quantum key distribution (QKD). Poor reconciliation e?ciency, revealing more information than strictly needed, may compromise the maximum attainable distance, while poor performance of the algorithm limits the practical throughput in a QKD device. Historically, reconciliation has been mainly done using close to minimal information disclosure but heavily interactive procedures, like Cascade, or using less e?cient but also less interactive ?just one message is exchanged? procedures, like the ones based in low-density parity-check (LDPC) codes. The price to pay in the LDPC case is that good e?ciency is only attained for very long codes and in a very narrow range centered around the quantum bit error rate (QBER) that the code was designed to reconcile, thus forcing to have several codes if a broad range of QBER needs to be catered for. Real world implementations of these methods are thus very demanding, either on computational or communication resources or both, to the extent that the last generation of GHz clocked QKD systems are ?nding a bottleneck in the classical part. In order to produce compact, high performance and reliable QKD systems it would be highly desirable to remove these problems. Here we analyse the use of short-length LDPC codes in the information reconciliation context using a low interactivity, blind, protocol that avoids an a priori error rate estimation. We demonstrate that 2×103 bits length LDPC codes are suitable for blind reconciliation. Such codes are of high interest in practice, since they can be used for hardware implementations with very high throughput.

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Due to the relative transparency of its embryos and larvae, the zebrafish is an ideal model organism for bioimaging approaches in vertebrates. Novel microscope technologies allow the imaging of developmental processes in unprecedented detail, and they enable the use of complex image-based read-outs for high-throughput/high-content screening. Such applications can easily generate Terabytes of image data, the handling and analysis of which becomes a major bottleneck in extracting the targeted information. Here, we describe the current state of the art in computational image analysis in the zebrafish system. We discuss the challenges encountered when handling high-content image data, especially with regard to data quality, annotation, and storage. We survey methods for preprocessing image data for further analysis, and describe selected examples of automated image analysis, including the tracking of cells during embryogenesis, heartbeat detection, identification of dead embryos, recognition of tissues and anatomical landmarks, and quantification of behavioral patterns of adult fish. We review recent examples for applications using such methods, such as the comprehensive analysis of cell lineages during early development, the generation of a three-dimensional brain atlas of zebrafish larvae, and high-throughput drug screens based on movement patterns. Finally, we identify future challenges for the zebrafish image analysis community, notably those concerning the compatibility of algorithms and data formats for the assembly of modular analysis pipelines.

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We report a general method for screening, in solution, the impact of deviations from canonical Watson-Crick composition on the thermodynamic stability of nucleic acid duplexes. We demonstrate how fluorescence resonance energy transfer (FRET) can be used to detect directly free energy differences between an initially formed “reference” duplex (usually a Watson-Crick duplex) and a related “test” duplex containing a lesion/alteration of interest (e.g., a mismatch, a modified, a deleted, or a bulged base, etc.). In one application, one titrates into a solution containing a fluorescently labeled, FRET-active, reference duplex, an unlabeled, single-stranded nucleic acid (test strand), which may or may not compete successfully to form a new duplex. When a new duplex forms by strand displacement, it will not exhibit FRET. The resultant titration curve (normalized fluorescence intensity vs. logarithm of test strand concentration) yields a value for the difference in stability (free energy) between the newly formed, test strand-containing duplex and the initial reference duplex. The use of competitive equilibria in this assay allows the measurement of equilibrium association constants that far exceed the magnitudes accessible by conventional titrimetric techniques. Additionally, because of the sensitivity of fluorescence, the method requires several orders of magnitude less material than most other solution methods. We discuss the advantages of this method for detecting and characterizing any modification that alters duplex stability, including, but not limited to, mutagenic lesions. We underscore the wide range of accessible free energy values that can be defined by this method, the applicability of the method in probing for a myriad of nucleic acid variations, such as single nucleotide polymorphisms, and the potential of the method for high throughput screening.

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The transcription factor nuclear factor κB (NFκB) is a key factor in the immune response triggered by a wide variety of molecules such as inflammatory cytokines, or some bacterial and viral products. This transcription factor represents a new target for the development of anti-inflammatory molecules, but this type of research is currently hampered by the lack of a convenient and rapid screening assay for NFκB activation. Indeed, NFκB DNA-binding capacity is traditionally estimated by radioactive gel shift assay. Here we propose a new DNA-binding assay based on the use of multi-well plates coated with a cold oligonucleotide containing the consensus binding site for NFκB. The presence of the DNA-bound transcription factor is then detected by anti-NFκB antibodies and revealed by colorimetry. This assay is easy to use, non-radioactive, highly reproducible, specific for NFκB, more sensitive than regular radioactive gel shift and very convenient for high throughput screening.

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Here we present the successful application of the microarray technology platform to the analysis of DNA polymorphisms. Using the rice genome as a model, we demonstrate the potential of a high-throughput genome analysis method called Diversity Array Technology, DArT‘. In the format presented here the technology is assaying for the presence (or amount) of a specific DNA fragment in a representation derived from the total genomic DNA of an organism or a population of organisms. Two different approaches are presented: the first involves contrasting two representations on a single array while the second involves contrasting a representation with a reference DNA fragment common to all elements of the array. The Diversity Panels created using this method allow genetic fingerprinting of any organism or group of organisms belonging to the gene pool from which the panel was developed. Diversity Arrays enable rapid and economical application of a highly parallel, solid-state genotyping technology to any genome or complex genomic mixtures.

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The Biomolecular Interaction Network Database (BIND; http://binddb.org) is a database designed to store full descriptions of interactions, molecular complexes and pathways. Development of the BIND 2.0 data model has led to the incorporation of virtually all components of molecular mechanisms including interactions between any two molecules composed of proteins, nucleic acids and small molecules. Chemical reactions, photochemical activation and conformational changes can also be described. Everything from small molecule biochemistry to signal transduction is abstracted in such a way that graph theory methods may be applied for data mining. The database can be used to study networks of interactions, to map pathways across taxonomic branches and to generate information for kinetic simulations. BIND anticipates the coming large influx of interaction information from high-throughput proteomics efforts including detailed information about post-translational modifications from mass spectrometry. Version 2.0 of the BIND data model is discussed as well as implementation, content and the open nature of the BIND project. The BIND data specification is available as ASN.1 and XML DTD.

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High throughput genome (HTG) and expressed sequence tag (EST) sequences are currently the most abundant nucleotide sequence classes in the public database. The large volume, high degree of fragmentation and lack of gene structure annotations prevent efficient and effective searches of HTG and EST data for protein sequence homologies by standard search methods. Here, we briefly describe three newly developed resources that should make discovery of interesting genes in these sequence classes easier in the future, especially to biologists not having access to a powerful local bioinformatics environment. trEST and trGEN are regularly regenerated databases of hypothetical protein sequences predicted from EST and HTG sequences, respectively. Hits is a web-based data retrieval and analysis system providing access to precomputed matches between protein sequences (including sequences from trEST and trGEN) and patterns and profiles from Prosite and Pfam. The three resources can be accessed via the Hits home page (http://hits.isb-sib.ch).

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Early detection is an effective means of reducing cancer mortality. Here, we describe a highly sensitive high-throughput screen that can identify panels of markers for the early detection of solid tumor cells disseminated in peripheral blood. The method is a two-step combination of differential display and high-sensitivity cDNA arrays. In a primary screen, differential display identified 170 candidate marker genes differentially expressed between breast tumor cells and normal breast epithelial cells. In a secondary screen, high-sensitivity arrays assessed expression levels of these genes in 48 blood samples, 22 from healthy volunteers and 26 from breast cancer patients. Cluster analysis identified a group of 12 genes that were elevated in the blood of cancer patients. Permutation analysis of individual genes defined five core genes (P ≤ 0.05, permax test). As a group, the 12 genes generally distinguished accurately between healthy volunteers and patients with breast cancer. Mean expression levels of the 12 genes were elevated in 77% (10 of 13) untreated invasive cancer patients, whereas cluster analysis correctly classified volunteers and patients (P = 0.0022, Fisher's exact test). Quantitative real-time PCR confirmed array results and indicated that the sensitivity of the assay (1:2 × 108 transcripts) was sufficient to detect disseminated solid tumor cells in blood. Expression-based blood assays developed with the screening approach described here have the potential to detect and classify solid tumor cells originating from virtually any primary site in the body.

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The key requirements for high-throughput single-nucleotide polymorphism (SNP) typing of DNA samples in large-scale disease case-control studies are automatability, simplicity, and robustness, coupled with minimal cost. In this paper we describe a fluorescence technique for the detection of SNPs that have been amplified by using the amplification refractory mutation system (ARMS)-PCR procedure. Its performance was evaluated using 32 sequence-specific primer mixes to assign the HLA-DRB alleles to 80 lymphoblastoid cell line DNAs chosen from our database for their diversity. All had been typed previously by alternative methods, either direct sequencing or gel electrophoresis. We believe the detection system that we call AMDI (alkaline-mediated differential interaction) satisfies the above criteria and is suitable for general high-throughput SNP typing.

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Detection of loss of heterozygosity (LOH) by comparison of normal and tumor genotypes using PCR-based microsatellite loci provides considerable advantages over traditional Southern blotting-based approaches. However, current methodologies are limited by several factors, including the numbers of loci that can be evaluated for LOH in a single experiment, the discrimination of true alleles versus "stutter bands," and the use of radionucleotides in detecting PCR products. Here we describe methods for high throughput simultaneous assessment of LOH at multiple loci in human tumors; these methods rely on the detection of amplified microsatellite loci by fluorescence-based DNA sequencing technology. Data generated by this approach are processed by several computer software programs that enable the automated linear quantitation and calculation of allelic ratios, allowing rapid ascertainment of LOH. As a test of this approach, genotypes at a series of loci on chromosome 4 were determined for 58 carcinomas of the uterine cervix. The results underscore the efficacy, sensitivity, and remarkable reproducibility of this approach to LOH detection and provide subchromosomal localization of two regions of chromosome 4 commonly altered in cervical tumors.

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The ability to carry out high-resolution genetic mapping at high throughput in the mouse is a critical rate-limiting step in the generation of genetically anchored contigs in physical mapping projects and the mapping of genetic loci for complex traits. To address this need, we have developed an efficient, high-resolution, large-scale genome mapping system. This system is based on the identification of polymorphic DNA sites between mouse strains by using interspersed repetitive sequence (IRS) PCR. Individual cloned IRS PCR products are hybridized to a DNA array of IRS PCR products derived from the DNA of individual mice segregating DNA sequences from the two parent strains. Since gel electrophoresis is not required, large numbers of samples can be genotyped in parallel. By using this approach, we have mapped > 450 polymorphic probes with filters containing the DNA of up to 517 backcross mice, potentially allowing resolution of 0.14 centimorgan. This approach also carries the potential for a high degree of efficiency in the integration of physical and genetic maps, since pooled DNAs representing libraries of yeast artificial chromosomes or other physical representations of the mouse genome can be addressed by hybridization of filter representations of the IRS PCR products of such libraries.

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A cardiomiopatia hipertrófica (CMH) é uma doença geneticamente determinada, caracterizada por hipertrofia ventricular primária, com prevalência estimada de 0.2% na população geral. Qualquer portador tem 50% de chance de transmitir esta doença para seus filhos, o que torna cada vez mais relevante a importância do estudo genético dos indivíduos acometidos e de seus familiares. Já foram descritas diversas mutações genéticas causadoras de CMH, a maioria em genes que codificam proteínas do sarcômero, e algumas mutações mais raras em genes não sarcoméricos. O objetivo desse estudo é sequenciar as regiões exônicas de genes candidatos, incluindo os principais envolvidos na hipertrofia miocárdica, utilizando o sequenciamento de nova geração (Generation Sequencing); testar a aplicabilidade e viabilidade deste sistema para identificar mutações já confirmadas e propor as prováveis novas mutações causadoras de CMH. Métodos e resultados: 66 pacientes não aparentados portadores de CMH foram estudados e submetidos à coleta de sangue para obtenção do DNA para analisar as regiões exômicas de 82 genes candidatos, utilizando a plataforma MiSeq (Illumina). Identificou-se 99 mutações provavelmente patogênicas em 54 pacientes incluídos no estudo (81,8%) relacionadas ou não a CMH, e distribuídas em 42 genes diferentes. Destas mutações 27 já haviam sido publicadas, sendo que 17 delas descritas como causadoras de CMH. Em 28 pacientes (42,4%) identificou-se mutação nos três principais genes sarcoméricos relacionados à CMH (MYH7, MYBPC3, TNNT2). Encontrou-se também um grande número de variantes não sonôminas de efeito clínico incerto e algumas mutações relacionadas a outras enfermidades. Conclusão: a análise da sequencia dos exônos de genes candidatos, demonstrou ser uma técnica promissora para o diagnóstico genético de CMH de forma mais rápida e sensível. A quantidade de dados gerados é o um fator limitante até o momento, principalmente em doenças geneticamente complexas com envolvimento de diversos genes e com sistema de bioinformática limitado.

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Climatic change is an increasing challenge for agriculture that is driving the development of suitable crops in order to ensure supply for both human nutrition and animal feed. In this context, it is increasingly important to understand the biochemical responses of cells to environmental cues at the whole system level, an aim that is being brought closer by advances in high throughput, cost-efficient plant metabolomics. To support molecular breeding activities, we have assessed the economic, technical and statistical feasibility of using direct mass spectrometry methods to evaluate the physiological state of maize (Zea mays L.) plants grown under different stress conditions.

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Objectives: Cyclosporin is an immunosuppressant drug with a narrow therapeutic window. Trough and 2-h post-dose blood samples are currently used for therapeutic drug monitoring in solid organ transplant recipients. The aim of the current study was to develop a rapid HPLC-tandem mass spectrometry (HPLC-MS) method for the measurement of cyclosporin in whole blood that was not only suitable for the clinical setting but also considered a reference method. Methods: Blood samples (50 mu L) were prepared by protein precipitation followed by C-18 solid-phase extraction while using d(12) cyclosporin as the internal standard. Mass spectrometric detection was by selected reaction monitoring with an electrospray interface in positive ionization mode. Results: The assay was linear from 10 to 2000 mu g/L (r(2) > 0.996, n = 9). Inter-day,analytical recovery and imprecision using whole blood quality control samples at 10, 30, 400, 1500, and 2000 mu g/L were 94.9-103.5% and

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Organosilica microspheres synthesised via a novel surfactant-free emulsion-based method show applicability towards optical encoding, solid-phase synthesis and high-throughput screening of bound oligonucleotide and peptide sequences.