1,549 research outputs found

    Neural network design and feature selection using principal component analysis and Taguchi method for identifying wood veneer defects

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    Nowadays, ensuring high quality can be considered the main strength for a company’s success. Especially, in a period of economic recession, quality control is crucial from the operational and strategic point of view. There are different quality control methods and it has been proven that on the whole companies using a continuous improvement approach, eliminating waste and maximizing productive flow, are more efficient and produce more with lower costs. This paper presents a method to optimize the quality control stage for a wood manufacturing firm. The method is based on the employment of the principal component analysis in order to reduce the number of critical variables to be given as input for an artificial neural network (ANN) to identify wood veneer defects. The proposed method allows the ANN classifier to identify defects in real time and increase the response speed during the quality control stage so that veneers with defects do not pass through the whole production cycle but are rejected at the beginning

    Identification and removal of low-complexity sites in allele-specific analysis of ChIP-seq data

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    Motivation: High-throughput sequencing technologies enable the genome-wide analysis of the impact of genetic variation on molecular phenotypes at unprecedented resolution. However, although powerful, these technologies can also introduce unexpected artifacts. Results: We investigated the impact of library amplification bias on the identification of allele-specific (AS) molecular events from high-throughput sequencing data derived from chromatin immunoprecipitation assays (ChIP-seq). Putative AS DNA binding activity for RNA polymerase II was determined using ChIP-seq data derived from lymphoblastoid cell lines of two parent-daughter trios. We found that, at high-sequencing depth, many significant AS binding sites suffered from an amplification bias, as evidenced by a larger number of clonal reads representing one of the two alleles. To alleviate this bias, we devised an amplification bias detection strategy, which filters out sites with low read complexity and sites featuring a significant excess of clonal reads. This method will be useful for AS analyses involving ChIP-seq and other functional sequencing assays. Availability: The R package absfilter for library clonality simulations and detection of amplification-biased sites is available from http://updepla1srv1.epfl.ch/waszaks/absfilter Contact: [email protected] or [email protected] Supplementary information: Supplementary data are available at Bioinformatics onlin

    Homozygosity for a missense mutation in the 67 kDa isoform of glutamate decarboxylase in a family with autosomal recessive spastic cerebral palsy: parallels with Stiff-Person Syndrome and other movement disorders

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    Background Cerebral palsy (CP) is an heterogeneous group of neurological disorders of movement and/or posture, with an estimated incidence of 1 in 1000 live births. Non-progressive forms of symmetrical, spastic CP have been identified, which show a Mendelian autosomal recessive pattern of inheritance. We recently described the mapping of a recessive spastic CP locus to a 5 cM chromosomal region located at 2q24-31.1, in rare consanguineous families. Methods Here we present data that refine this locus to a 0.5 cM region, flanked by the microsatellite markers D2S2345 and D2S326. The minimal region contains the candidate gene GAD1, which encodes a glutamate decarboxylase isoform (GAD67), involved in conversion of the amino acid and excitatory neurotransmitter glutamate to the inhibitory neurotransmitter γ-aminobutyric acid (GABA). Results A novel amino acid mis-sense mutation in GAD67 was detected, which segregated with CP in affected individuals. Conclusions This result is interesting because auto-antibodies to GAD67 and the more widely studied GAD65 homologue encoded by the GAD2 gene, are described in patients with Stiff-Person Syndrome (SPS), epilepsy, cerebellar ataxia and Batten disease. Further investigation seems merited of the possibility that variation in the GAD1 sequence, potentially affecting glutamate/GABA ratios, may underlie this form of spastic CP, given the presence of anti-GAD antibodies in SPS and the recognised excitotoxicity of glutamate in various contexts

    Population substructure in Finland and Sweden revealed by the use of spatial coordinates and a small number of unlinked autosomal SNPs

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    Abstract Background Despite several thousands of years of close contacts, there are genetic differences between the neighbouring countries of Finland and Sweden. Within Finland, signs of an east-west duality have been observed, whereas the population structure within Sweden has been suggested to be more subtle. With a fine-scale substructure like this, inferring the cluster membership of individuals requires a large number of markers. However, some studies have suggested that this number could be reduced if the individual spatial coordinates are taken into account in the analysis. Results We genotyped 34 unlinked autosomal single nucleotide polymorphisms (SNPs), originally designed for zygosity testing, from 2044 samples from Sweden and 657 samples from Finland, and 30 short tandem repeats (STRs) from 465 Finnish samples. We saw significant population structure within Finland but not between the countries or within Sweden, and isolation by distance within Finland and between the countries. In Sweden, we found a deficit of heterozygotes that we could explain by simulation studies to be due to both a small non-random genotyping error and hidden substructure caused by immigration. Geneland, a model-based Bayesian clustering algorithm, clustered the individuals into groups that corresponded to Sweden and Eastern and Western Finland when spatial coordinates were used, whereas in the absence of spatial information, only one cluster was inferred. Conclusion We show that the power to cluster individuals based on their genetic similarity is increased when including information about the spatial coordinates. We also demonstrate the importance of estimating the size and effect of genotyping error in population genetics in order to strengthen the validity of the results.</p

    Fifteen new risk loci for coronary artery disease highlight arterial-wall-specific mechanisms

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    Coronary artery disease (CAD) is a leading cause of morbidity and mortality worldwide. Although 58 genomic regions have been associated with CAD thus far, most of the heritability is unexplained, indicating that additional susceptibility loci await identification. An efficient discovery strategy may be larger-scale evaluation of promising associations suggested by genome-wide association studies (GWAS). Hence, we genotyped 56,309 participants using a targeted gene array derived from earlier GWAS results and performed meta-analysis of results with 194,427 participants previously genotyped, totaling 88,192 CAD cases and 162,544 controls. We identified 25 new SNP-CAD associations (P &lt; 5 × 10(-8), in fixed-effects meta-analysis) from 15 genomic regions, including SNPs in or near genes involved in cellular adhesion, leukocyte migration and atherosclerosis (PECAM1, rs1867624), coagulation and inflammation (PROCR, rs867186 (p.Ser219Gly)) and vascular smooth muscle cell differentiation (LMOD1, rs2820315). Correlation of these regions with cell-type-specific gene expression and plasma protein levels sheds light on potential disease mechanisms

    Genetic determinants of co-accessible chromatin regions in activated T cells across humans.

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    Over 90% of genetic variants associated with complex human traits map to non-coding regions, but little is understood about how they modulate gene regulation in health and disease. One possible mechanism is that genetic variants affect the activity of one or more cis-regulatory elements leading to gene expression variation in specific cell types. To identify such cases, we analyzed ATAC-seq and RNA-seq profiles from stimulated primary CD4+ T cells in up to 105 healthy donors. We found that regions of accessible chromatin (ATAC-peaks) are co-accessible at kilobase and megabase resolution, consistent with the three-dimensional chromatin organization measured by in situ Hi-C in T cells. Fifteen percent of genetic variants located within ATAC-peaks affected the accessibility of the corresponding peak (local-ATAC-QTLs). Local-ATAC-QTLs have the largest effects on co-accessible peaks, are associated with gene expression and are enriched for autoimmune disease variants. Our results provide insights into how natural genetic variants modulate cis-regulatory elements, in isolation or in concert, to influence gene expression

    Pan-Eurasian Experiment (PEEX): Towards a holistic understanding of the feedbacks and interactions in the land-Atmosphere-ocean-society continuum in the northern Eurasian region

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    The northern Eurasian regions and Arctic Ocean will very likely undergo substantial changes during the next decades. The Arctic-boreal natural environments play a crucial role in the global climate via albedo change, carbon sources and sinks as well as atmospheric aerosol production from biogenic volatile organic compounds. Furthermore, it is expected that global trade activities, demographic movement, and use of natural resources will be increasing in the Arctic regions. There is a need for a novel research approach, which not only identifies and tackles the relevant multi-disciplinary research questions, but also is able to make a holistic system analysis of the expected feedbacks. In this paper, we introduce the research agenda of the Pan-Eurasian Experiment (PEEX), a multi-scale, multi-disciplinary and international program started in 2012 (https://www.atm.helsinki.fi/peex/). PEEX sets a research approach by which large-scale research topics are investigated from a system perspective and which aims to fill the key gaps in our understanding of the feedbacks and interactions between the land-Atmosphere-Aquatic-society continuum in the northern Eurasian region. We introduce here the state of the art for the key topics in the PEEX research agenda and present the future prospects of the research, which we see relevant in this context

    Detection of regulator genes and eQTLs in gene networks

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    Genetic differences between individuals associated to quantitative phenotypic traits, including disease states, are usually found in non-coding genomic regions. These genetic variants are often also associated to differences in expression levels of nearby genes (they are "expression quantitative trait loci" or eQTLs for short) and presumably play a gene regulatory role, affecting the status of molecular networks of interacting genes, proteins and metabolites. Computational systems biology approaches to reconstruct causal gene networks from large-scale omics data have therefore become essential to understand the structure of networks controlled by eQTLs together with other regulatory genes, and to generate detailed hypotheses about the molecular mechanisms that lead from genotype to phenotype. Here we review the main analytical methods and softwares to identify eQTLs and their associated genes, to reconstruct co-expression networks and modules, to reconstruct causal Bayesian gene and module networks, and to validate predicted networks in silico.Comment: minor revision with typos corrected; review article; 24 pages, 2 figure

    Maternal and child cytokine relationship in early life is not altered by cytokine gene polymorphisms

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    The development of immune responses is influenced by the interaction between environmental and genetic factors. Our previous study showed a close association between maternal and young infant’s cytokine responses. The question is how this association evolves over time and the contribution of genetic polymorphisms to this association. Five cytokines in mitogen-stimulated whole blood culture were measured from pregnant mothers and their children aged 2, 5, 12, 24 and 48 months. Cytokine gene polymorphisms were determined in both mothers and children. High production of maternal interleukin (IL)-10, tumour necrosis factor-α (TNF-α) and interferon-γ (IFN-γ) was significantly associated with higher levels of the corresponding cytokines in their children at 2 months (T2), but the association decreased over time. Maternal single-nucleotide polymorphism (SNP) in IFN-γ gene, rs3181032, was found to be associated with child’s IFN-γ levels at T2 only, whereas maternal IL-10 rs4579758 and child’s TNF-α rs13215091 were associated with child’s corresponding cytokines at later ages but not at T2. In the final models including the gene polymorphisms, maternal cytokines were still the strongest determinant of child cytokines. Maternal cytokine during pregnancy, which could be a proxy for child’s environmental factors, showed its highest impact at early age, with no or little influence from genetic factors
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