904 resultados para Network Analysis Methods
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Today, many of Iowa’s counties are experiencing an increase in rural development. Two specific types of development were focused on for this research: rural residential subdivisions and livestock production operations. Rural residential developments are primarily year round single-family homes, though some are vacation homes. Livestock production in Iowa includes hog, beef, and poultry facilities. These two types of rural development, while obviously very different in nature and incompatible with each other, share one important characteristic: They each generate substantial amounts of new traffic for Iowa’s extensive secondary road system. This research brings together economic, spatial, and legal analysis methods to address the impacts of rural development on the secondary road system and provide county engineers, county supervisors, and state legislators with guidance in addressing the challenges associated with this development.
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Abstract: Inverse decision analysis methods in enviromental decision-making - inverse methods
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DNA-binding proteins mediate a variety of crucial molecular functions, such as transcriptional regulation and chromosome maintenance, replication and repair, which in turn control cell division and differentiation. The roles of these proteins in disease are currently being investigated using microarray-based approaches. However, these assays can be difficult to adapt to routine diagnosis of complex diseases such as cancer. Here, we review promising alternative approaches involving protein-binding microarrays (PBMs) that probe the interaction of proteins from crude cell or tissue extracts with large collections of synthetic or natural DNA sequences. Recent studies have demonstrated the use of these novel PBM approaches to provide rapid and unbiased characterization of DNA-binding proteins as molecular markers of disease, for example cancer progression or infectious diseases.
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Since the early days of functional magnetic resonance imaging (fMRI), retinotopic mapping emerged as a powerful and widely-accepted tool, allowing the identification of individual visual cortical fields and furthering the study of visual processing. In contrast, tonotopic mapping in auditory cortex proved more challenging primarily because of the smaller size of auditory cortical fields. The spatial resolution capabilities of fMRI have since advanced, and recent reports from our labs and several others demonstrate the reliability of tonotopic mapping in human auditory cortex. Here we review the wide range of stimulus procedures and analysis methods that have been used to successfully map tonotopy in human auditory cortex. We point out that recent studies provide a remarkably consistent view of human tonotopic organisation, although the interpretation of the maps continues to vary. In particular, there remains controversy over the exact orientation of the primary gradients with respect to Heschl's gyrus, which leads to different predictions about the location of human A1, R, and surrounding fields. We discuss the development of this debate and argue that literature is converging towards an interpretation that core fields A1 and R fold across the rostral and caudal banks of Heschl's gyrus, with tonotopic gradients laid out in a distinctive V-shaped manner. This suggests an organisation that is largely homologous with non-human primates. This article is part of a Special Issue entitled Human Auditory Neuroimaging.
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Organic matter plays an important role in many soil properties, and for that reason it is necessary to identify management systems which maintain or increase its concentrations. The aim of the present study was to determine the quality and quantity of organic C in different compartments of the soil fraction in different Amazonian ecosystems. The soil organic matter (FSOM) was fractionated and soil C stocks were estimated in primary forest (PF), pasture (P), secondary succession (SS) and an agroforestry system (AFS). Samples were collected at the depths 0-5, 5-10, 10-20, 20-40, 40-60, 60-80, 80-100, 100-160, and 160-200 cm. Densimetric and particle size analysis methods were used for FSOM, obtaining the following fractions: FLF (free light fraction), IALF (intra-aggregate light fraction), F-sand (sand fraction), F-clay (clay fraction) and F-silt (silt fraction). The 0-5 cm layer contains 60 % of soil C, which is associated with the FLF. The F-clay was responsible for 70 % of C retained in the 0-200 cm depth. There was a 12.7 g kg-1 C gain in the FLF from PF to SS, and a 4.4 g kg-1 C gain from PF to AFS, showing that SS and AFS areas recover soil organic C, constituting feasible C-recovery alternatives for degraded and intensively farmed soils in Amazonia. The greatest total stocks of carbon in soil fractions were, in decreasing order: (101.3 Mg ha-1 of C - AFS) > (98.4 Mg ha-1 of C - FP) > (92.9 Mg ha-1 of C - SS) > (64.0 Mg ha-1 of C - P). The forms of land use in the Amazon influence C distribution in soil fractions, resulting in short- or long-term changes.
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Genome-wide association studies have been instrumental in identifying genetic variants associated with complex traits such as human disease or gene expression phenotypes. It has been proposed that extending existing analysis methods by considering interactions between pairs of loci may uncover additional genetic effects. However, the large number of possible two-marker tests presents significant computational and statistical challenges. Although several strategies to detect epistasis effects have been proposed and tested for specific phenotypes, so far there has been no systematic attempt to compare their performance using real data. We made use of thousands of gene expression traits from linkage and eQTL studies, to compare the performance of different strategies. We found that using information from marginal associations between markers and phenotypes to detect epistatic effects yielded a lower false discovery rate (FDR) than a strategy solely using biological annotation in yeast, whereas results from human data were inconclusive. For future studies whose aim is to discover epistatic effects, we recommend incorporating information about marginal associations between SNPs and phenotypes instead of relying solely on biological annotation. Improved methods to discover epistatic effects will result in a more complete understanding of complex genetic effects.
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Amplified Fragment Length Polymorphisms (AFLPs) are a cheap and efficient protocol for generating large sets of genetic markers. This technique has become increasingly used during the last decade in various fields of biology, including population genomics, phylogeography, and genome mapping. Here, we present RawGeno, an R library dedicated to the automated scoring of AFLPs (i.e., the coding of electropherogram signals into ready-to-use datasets). Our program includes a complete suite of tools for binning, editing, visualizing, and exporting results obtained from AFLP experiments. RawGeno can either be used with command lines and program analysis routines or through a user-friendly graphical user interface. We describe the whole RawGeno pipeline along with recommendations for (a) setting the analysis of electropherograms in combination with PeakScanner, a program freely distributed by Applied Biosystems; (b) performing quality checks; (c) defining bins and proceeding to scoring; (d) filtering nonoptimal bins; and (e) exporting results in different formats.
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The function of DNA-binding proteins is controlled not just by their abundance, but mainly at the level of their activity in terms of their interactions with DNA and protein targets. Moreover, the affinity of such transcription factors to their target sequences is often controlled by co-factors and/or modifications that are not easily assessed from biological samples. Here, we describe a scalable method for monitoring protein-DNA interactions on a microarray surface. This approach was designed to determine the DNA-binding activity of proteins in crude cell extracts, complementing conventional expression profiling arrays. Enzymatic labeling of DNA enables direct normalization of the protein binding to the microarray, allowing the estimation of relative binding affinities. Using DNA sequences covering a range of affinities, we show that the new microarray-based method yields binding strength estimates similar to low-throughput gel mobility-shift assays. The microarray is also of high sensitivity, as it allows the detection of a rare DNA-binding protein from breast cancer cells, the human tumor suppressor AP-2. This approach thus mediates precise and robust assessment of the activity of DNA-binding proteins and takes present DNA-binding assays to a high throughput level.
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Renal excretion of water and major electrolytes exhibits a significant circadian rhythm. This functional periodicity is believed to result, at least in part, from circadian changes in secretion/reabsorption capacities of the distal nephron and collecting ducts. Here, we studied the molecular mechanisms underlying circadian rhythms in the distal nephron segments, i.e., distal convoluted tubule (DCT) and connecting tubule (CNT) and the cortical collecting duct (CCD). Temporal expression analysis performed on microdissected mouse DCT/CNT or CCD revealed a marked circadian rhythmicity in the expression of a large number of genes crucially involved in various homeostatic functions of the kidney. This analysis also revealed that both DCT/CNT and CCD possess an intrinsic circadian timing system characterized by robust oscillations in the expression of circadian core clock genes (clock, bma11, npas2, per, cry, nr1d1) and clock-controlled Par bZip transcriptional factors dbp, hlf, and tef. The clock knockout mice or mice devoid of dbp/hlf/tef (triple knockout) exhibit significant changes in renal expression of several key regulators of water or sodium balance (vasopressin V2 receptor, aquaporin-2, aquaporin-4, alphaENaC). Functionally, the loss of clock leads to a complex phenotype characterized by partial diabetes insipidus, dysregulation of sodium excretion rhythms, and a significant decrease in blood pressure. Collectively, this study uncovers a major role of molecular clock in renal function.
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Profiling microRNA (miRNA) expression is of widespread interest given the critical role of miRNAs in many cellular functions. Profiling can be achieved via hybridization-based (microarrays), sequencing-based, or amplification-based (quantitative reverse transcription-PCR, qPCR) technologies. Among these, microarrays face the significant challenge of accurately distinguishing between mature and immature miRNA forms, and different vendors have developed different methods to meet this challenge. Here we measure differential miRNA expression using the Affymetrix, Agilent, and Illumina microarray platforms, as well as qPCR (Applied Biosystems) and ultra high-throughput sequencing (Illumina). We show that the differential expression measurements are more divergent when the three types of microarrays are compared than when the Agilent microarray, qPCR, and sequencing technology measurements are compared, which exhibit a good overall concordance.
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INTRODUCTION: Triple-negative breast cancers (TNBCs) are characterised by lack of expression of hormone receptors and epidermal growth factor receptor 2 (HER-2). As they frequently express epidermal growth factor receptors (EGFRs), anti-EGFR therapies are currently assessed for this breast cancer subtype as an alternative to treatments that target HER-2 or hormone receptors. Recently, EGFR-activating mutations have been reported in TNBC specimens in an East Asian population. Because variations in the frequency of EGFR-activating mutations in East Asians and other patients with lung cancer have been described, we evaluated the EGFR mutational profile in tumour samples from European patients with TNBC. METHODS: We selected from a DNA tumour bank 229 DNA samples isolated from frozen, histologically proven and macrodissected invasive TNBC specimens from European patients. PCR and high-resolution melting (HRM) analyses were used to detect mutations in exons 19 and 21 of EGFR. The results were then confirmed by bidirectional sequencing of all samples. RESULTS: HRM analysis allowed the detection of three EGFR exon 21 mutations, but no exon 19 mutations. There was 100% concordance between the HRM and sequencing results. The three patients with EGFR exon 21 abnormal HRM profiles harboured the rare R836R SNP, but no EGFR-activating mutation was identified. CONCLUSIONS: This study highlights variations in the prevalence of EGFR mutations in TNBC. These variations have crucial implications for the design of clinical trials involving anti-EGFR treatments in TNBC and for identifying the potential target population.
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In this tutorial review, we detail both the rationale for as well as the implementation of a set of analyses of surface-recorded event-related potentials (ERPs) that uses the reference-free spatial (i.e. topographic) information available from high-density electrode montages to render statistical information concerning modulations in response strength, latency, and topography both between and within experimental conditions. In these and other ways these topographic analysis methods allow the experimenter to glean additional information and neurophysiologic interpretability beyond what is available from canonical waveform analyses. In this tutorial we present the example of somatosensory evoked potentials (SEPs) in response to stimulation of each hand to illustrate these points. For each step of these analyses, we provide the reader with both a conceptual and mathematical description of how the analysis is carried out, what it yields, and how to interpret its statistical outcome. We show that these topographic analysis methods are intuitive and easy-to-use approaches that can remove much of the guesswork often confronting ERP researchers and also assist in identifying the information contained within high-density ERP datasets
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Motivation: Genome-wide association studies have become widely used tools to study effects of genetic variants on complex diseases. While it is of great interest to extend existing analysis methods by considering interaction effects between pairs of loci, the large number of possible tests presents a significant computational challenge. The number of computations is further multiplied in the study of gene expression quantitative trait mapping, in which tests are performed for thousands of gene phenotypes simultaneously. Results: We present FastEpistasis, an efficient parallel solution extending the PLINK epistasis module, designed to test for epistasis effects when analyzing continuous phenotypes. Our results show that the algorithm scales with the number of processors and offers a reduction in computation time when several phenotypes are analyzed simultaneously. FastEpistasis is capable of testing the association of a continuous trait with all single nucleotide polymorphism ( SNP) pairs from 500 000 SNPs, totaling 125 billion tests, in a population of 5000 individuals in 29, 4 or 0.5 days using 8, 64 or 512 processors.
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Diagnosis in allergology is facing novel challenges because of the availability not only of purified or recombinant allergens, but also of multitests such as allergen micro-arrays. These new diagnostic opportunities contribute to a better understanding of crossreactivities between respiratory and food allergens. In comparison to current diagnosis based on whole allergen extracts, this novel generation of specific IgE tests is expected to provide better information on the risk of reaction to allergens as well as on its severity. However these new technologies are expensive, and will have to be carefully analyzed in terms of medical usefulness and public health costs.