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  • 1
    Publication Date: 2012-03-29
    Description: Next-generation sequencing (NGS) technologies-based transcriptomic profiling method often called RNA-seq has been widely used to study global gene expression, alternative exon usage, new exon discovery, novel transcriptional isoforms and genomic sequence variations. However, this technique also poses many biological and informatics challenges to extracting meaningful biological information. The RNA-seq data analysis is built on the foundation of high quality initial genome localization and alignment information for RNA-seq sequences. Toward this goal, we have developed RNASEQR to accurately and effectively map millions of RNA-seq sequences. We have systematically compared RNASEQR with four of the most widely used tools using a simulated data set created from the Consensus CDS project and two experimental RNA-seq data sets generated from a human glioblastoma patient. Our results showed that RNASEQR yields more accurate estimates for gene expression, complete gene structures and new transcript isoforms, as well as more accurate detection of single nucleotide variants (SNVs). RNASEQR analyzes raw data from RNA-seq experiments effectively and outputs results in a manner that is compatible with a wide variety of specialized downstream analyses on desktop computers.
    Keywords: Computational Methods, Massively Parallel (Deep) Sequencing, Genomics
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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  • 2
    Publication Date: 2013-10-19
    Description: Identifying variants using high-throughput sequencing data is currently a challenge because true biological variants can be indistinguishable from technical artifacts. One source of technical artifact results from incorrectly aligning experimentally observed sequences to their true genomic origin (‘mismapping’) and inferring differences in mismapped sequences to be true variants. We developed BlackOPs, an open-source tool that simulates experimental RNA-seq and DNA whole exome sequences derived from the reference genome, aligns these sequences by custom parameters, detects variants and outputs a blacklist of positions and alleles caused by mismapping. Blacklists contain thousands of artifact variants that are indistinguishable from true variants and, for a given sample, are expected to be almost completely false positives. We show that these blacklist positions are specific to the alignment algorithm and read length used, and BlackOPs allows users to generate a blacklist specific to their experimental setup. We queried the dbSNP and COSMIC variant databases and found numerous variants indistinguishable from mapping errors. We demonstrate how filtering against blacklist positions reduces the number of potential false variants using an RNA-seq glioblastoma cell line data set. In summary, accounting for mapping-caused variants tuned to experimental setups reduces false positives and, therefore, improves genome characterization by high-throughput sequencing.
    Keywords: Computational Methods, Massively Parallel (Deep) Sequencing, Genomics
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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  • 3
    Publication Date: 2015-07-10
    Description: The dimensions that define a food product have expanded rapidly to include characteristics of the production process, marketing arrangements, and implications that production and consumption of the product have for the environment. Some market intermediaries have responded by requiring that their suppliers abide by restrictive production practices. We examine the economic effects of such restrictions and apply this analysis to limitations on the use of antibiotics in U.S. pork production. Results from conceptual and simulation analyses show that, in the absence of demand growth, less pork is sold due to higher costs in the restricted segment, and both pork consumers (on average) and producers are harmed. Demand growth of between 6–11% from adding new consumers who will consume the restricted (antibiotic-free) product but not the conventional product is needed to return consumer surplus to the level in the base case, and between 2–4% demand growth was required to return producer surplus to base. When restricted and conventional products are modeled using a vertical differentiation framework, results depend importantly on the ease with which consumers can switch to a seller who offers their desired product type. Significant distributional impacts among consumers are present when switching costs are prohibitive.
    Keywords: I18 - Government Policy ; Regulation ; Public Health, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness, Q18 - Agricultural Policy ; Food Policy
    Print ISSN: 0002-9092
    Electronic ISSN: 1467-8276
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 4
    Publication Date: 2012-12-28
    Description: We investigate the impact of decentralised decision-making on product quality. Comparing a cooperative and an investor-owned firm suggests that members of the cooperative have an incentive to produce too much and to free-ride on quality. Whether or not cooperatives deliver higher quality products depends on the way in which the quality of the final product is determined from the quality levels of the inputs delivered (quality aggregation) as well as the number of members of the cooperative. Empirical evidence on the Austrian wine market suggests that wines produced by cooperatives tend to be of significantly lower quality, ceteris paribus .
    Keywords: D22 - Firm Behavior: Empirical Analysis, D23 - Organizational Behavior ; Transaction Costs ; Property Rights, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness
    Print ISSN: 0165-1587
    Electronic ISSN: 1464-3618
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 5
    Publication Date: 2013-02-26
    Description: This paper explores the demand and willingness to pay (WTP) for value-added services to chicken. Since the demand for such services are likely to be highly segmented and often applies only to a market niche, models based on assumptions of homogeneity among consumers are likely to be inappropriate. For this reason, this paper combines discrete and continuous mixing distributions to concurrently identify the size of the niche market and the heterogeneity among consumers within the market niche. Failing to account for the niche market nature of value-added services is shown to have implications for predictions of WTP, demand and total revenue.
    Keywords: C25 - Discrete Regression and Qualitative Choice Models, D12 - Consumer Economics: Empirical Analysis, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness
    Print ISSN: 0165-1587
    Electronic ISSN: 1464-3618
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 6
    Publication Date: 2012-10-10
    Description: Several bioinformatics methods have been proposed for the detection and characterization of genomic structural variation (SV) from ultra high-throughput genome resequencing data. Recent surveys show that comprehensive detection of SV events of different types between an individual resequenced genome and a reference sequence is best achieved through the combination of methods based on different principles (split mapping, reassembly, read depth, insert size, etc.). The improvement of individual predictors is thus an important objective. In this study, we propose a new method that combines deviations from expected library insert sizes and additional information from local patterns of read mapping and uses supervised learning to predict the position and nature of structural variants. We show that our approach provides greatly increased sensitivity with respect to other tools based on paired end read mapping at no cost in specificity, and it makes reliable predictions of very short insertions and deletions in repetitive and low-complexity genomic contexts that can confound tools based on split mapping of reads.
    Keywords: Computational Methods, Massively Parallel (Deep) Sequencing, Genomics
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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  • 7
    Publication Date: 2015-09-12
    Description: Community Supported Agriculture (CSA) contracts allow consumers to buy claims on a farm's future production. In turn, the consumer provides working capital to the farm during the growing season. CSA contracts also provide risk management for farmers with limited access to Federal crop insurance by transferring part of the farm's risk to the consumer. We derive a theory of CSA contract pricing for the two most prevalent types of CSA contracts: yield contracts, in which consumers receive a percentage of the farm's production, and weight contracts, in which consumers receive fixed quantities. We develop a two-period model in which expected utility maximizing producers and consumers engage in CSA contracting in the first period based on anticipation of yields and spot prices in the second period. Using the model, we generate several testable hypotheses to be explored in future research. Additionally, we present an overview of the data necessary to test the propositions and potential challenges that might arise in related empirical work.
    Keywords: Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness, Q14 - Agricultural Finance
    Print ISSN: 0002-9092
    Electronic ISSN: 1467-8276
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 8
    Publication Date: 2012-06-28
    Description: We introduce Grinder ( http://sourceforge.net/projects/biogrinder/ ), an open-source bioinformatic tool to simulate amplicon and shotgun (genomic, metagenomic, transcriptomic and metatranscriptomic) datasets from reference sequences. This is the first tool to simulate amplicon datasets (e.g. 16S rRNA) widely used by microbial ecologists. Grinder can create sequence libraries with a specific community structure, α and β diversities and experimental biases (e.g. chimeras, gene copy number variation) for commonly used sequencing platforms. This versatility allows the creation of simple to complex read datasets necessary for hypothesis testing when developing bioinformatic software, benchmarking existing tools or designing sequence-based experiments. Grinder is particularly useful for simulating clinical or environmental microbial communities and complements the use of in vitro mock communities.
    Keywords: Computational Methods, Massively Parallel (Deep) Sequencing, Genomics
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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  • 9
    Publication Date: 2012-05-13
    Description: Numerous algorithms have been developed to analyze ChIP-Seq data. However, the complexity of analyzing diverse patterns of ChIP-Seq signals, especially for epigenetic marks, still calls for the development of new algorithms and objective comparisons of existing methods. We developed Qeseq, an algorithm to detect regions of increased ChIP read density relative to background. Qeseq employs critical novel elements, such as iterative recalibration and neighbor joining of reads to identify enriched regions of any length. To objectively assess its performance relative to other 14 ChIP-Seq peak finders, we designed a novel protocol based on Validation Discriminant Analysis (VDA) to optimally select validation sites and generated two validation datasets, which are the most comprehensive to date for algorithmic benchmarking of key epigenetic marks. In addition, we systematically explored a total of 315 diverse parameter configurations from these algorithms and found that typically optimal parameters in one dataset do not generalize to other datasets. Nevertheless, default parameters show the most stable performance, suggesting that they should be used. This study also provides a reproducible and generalizable methodology for unbiased comparative analysis of high-throughput sequencing tools that can facilitate future algorithmic development.
    Keywords: Computational Methods, Massively Parallel (Deep) Sequencing, Genomics
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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  • 10
    Publication Date: 2012-05-23
    Description: Deciphering the structure of gene regulatory networks across the tree of life remains one of the major challenges in postgenomic biology. We present a novel ChIP-seq workflow for the archaea using the model organism Halobacterium salinarum sp. NRC-1 and demonstrate its application for mapping the genome-wide binding sites of natively expressed transcription factors. This end-to-end pipeline is the first protocol for ChIP-seq in archaea, with methods and tools for each stage from gene tagging to data analysis and biological discovery. Genome-wide binding sites for transcription factors with many binding sites (TfbD) are identified with sensitivity, while retaining specificity in the identification the smaller regulons (bacteriorhodopsin-activator protein). Chromosomal tagging of target proteins with a compact epitope facilitates a standardized and cost-effective workflow that is compatible with high-throughput immunoprecipitation of natively expressed transcription factors. The Pique package, an open-source bioinformatics method, is presented for identification of binding events. Relative to ChIP-Chip and qPCR, this workflow offers a robust catalog of protein–DNA binding events with improved spatial resolution and significantly decreased cost. While this study focuses on the application of ChIP-seq in H. salinarum sp. NRC-1, our workflow can also be adapted for use in other archaea and bacteria with basic genetic tools.
    Keywords: Computational Methods, Massively Parallel (Deep) Sequencing, Genomics
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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