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  • 1
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    A novel essential domain perspective for exploring gene essentiality (2015)
    Oxford University Press
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    Publikationsdatum: 2015-09-11
    Beschreibung: Motivation: Genes with indispensable functions are identified as essential; however, the traditional gene-level studies of essentiality have several limitations. In this study, we characterized gene essentiality from a new perspective of protein domains, the independent structural or functional units of a polypeptide chain. Results: To identify such essential domains, we have developed an Expectation–Maximization (EM) algorithm-based Essential Domain Prediction (EDP) Model. With simulated datasets, the model provided convergent results given different initial values and offered accurate predictions even with noise. We then applied the EDP model to six microbial species and predicted 1879 domains to be essential in at least one species, ranging 10–23% in each species. The predicted essential domains were more conserved than either non-essential domains or essential genes. Comparing essential domains in prokaryotes and eukaryotes revealed an evolutionary distance consistent with that inferred from ribosomal RNA. When utilizing these essential domains to reproduce the annotation of essential genes, we received accurate results that suggest protein domains are more basic units for the essentiality of genes. Furthermore, we presented several examples to illustrate how the combination of essential and non-essential domains can lead to genes with divergent essentiality. In summary, we have described the first systematic analysis on gene essentiality on the level of domains. Contact: huilu.bioinfo@gmail.com or Long.Lu@cchmc.org Supplementary Information: Supplementary data are available at Bioinformatics online.
    Print ISSN: 1367-4803
    Digitale ISSN: 1460-2059
    Thema: Biologie , Informatik , Medizin
    Publiziert von Oxford University Press
    Standort Signatur Erwartet Verfügbarkeit
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  • 2
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    Deep models for brain EM image segmentation: novel insights and improved performance (2016)
    Oxford University Press
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    Publikationsdatum: 2016-07-30
    Beschreibung: Motivation: Accurate segmentation of brain electron microscopy (EM) images is a critical step in dense circuit reconstruction. Although deep neural networks (DNNs) have been widely used in a number of applications in computer vision, most of these models that proved to be effective on image classification tasks cannot be applied directly to EM image segmentation, due to the different objectives of these tasks. As a result, it is desirable to develop an optimized architecture that uses the full power of DNNs and tailored specifically for EM image segmentation. Results: In this work, we proposed a novel design of DNNs for this task. We trained a pixel classifier that operates on raw pixel intensities with no preprocessing to generate probability values for each pixel being a membrane or not. Although the use of neural networks in image segmentation is not completely new, we developed novel insights and model architectures that allow us to achieve superior performance on EM image segmentation tasks. Our submission based on these insights to the 2D EM Image Segmentation Challenge achieved the best performance consistently across all the three evaluation metrics. This challenge is still ongoing and the results in this paper are as of June 5, 2015. Availability and Implementation : https://github.com/ahmed-fakhry/dive Contact : sji@eecs.wsu.edu
    Print ISSN: 1367-4803
    Digitale ISSN: 1460-2059
    Thema: Biologie , Informatik , Medizin
    Publiziert von Oxford University Press
    Standort Signatur Erwartet Verfügbarkeit
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  • 3
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    Bioimage informatics: a new category in Bioinformatics (2012)
    Oxford University Press
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    Publikationsdatum: 2012-04-08
    Print ISSN: 1367-4803
    Digitale ISSN: 1460-2059
    Thema: Biologie , Informatik , Medizin
    Publiziert von Oxford University Press
    Standort Signatur Erwartet Verfügbarkeit
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  • 4
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    Tsc1 deficiency-mediated mTOR hyperactivation in vascular endothelial cells causes angiogenesis defects and embryonic lethality (2014)
    Oxford University Press
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    Publikationsdatum: 2014-01-11
    Beschreibung: This is a study on the role of tuberous sclerosis complex1 (TSC1) mutation and mTOR activation in endothelial cells during angiogenic and embryonic development. Past studies had shown that Tsc1/Tsc2 mutant genes lead to overactivation of mTOR in the regulating pathways in developing fetus. We used conditional Cre-loxp gene knockout approach to delete Tsc1 in mice's endothelial cells in our experimental models. Similarly, activation of mTOR signaling in endothelial cells of these embryos (Tie2-Cre/Tsc1 –/– ) was found. Majority of Tie2-Cre/Tsc1 –/– embryos died at embryonic day 14.5 in utero . Cardiovascular defects, subcutaneous edema and hemorrhage were present among them. Whole-mount immunostaining in these embryos revealed a disorganized vascular network, defective sprouting of vessels in yolk sac and thickening of the labyrinth layer in the placenta. A thinner ventricular wall with disorganized trabeculae was present in the hearts of Tie2-Cre/Tsc1 –/– embryos. Endothelial cells in Tsc1 -deficient mice showed defective mitochondrial and endoplasmic reticular morphology, but no significant change was observed in cell junctions. The mutant embryos displayed significantly reduced cell proliferation, increased apoptosis and disturbed expression of angiogenic factors. A cohort of mice was treated prenatally with mTOR inhibitor rapamycin. The offspring of these mutant mice survived up to 22 days after birth. It was concluded that physiological TSC1-mTOR signaling in endothelial cells is crucial for vascular development and embryogenesis. We postulated that disruption of normal angiogenic pathways through hyperactive mTOR signaling maybe the mechanism that lead to deranged vascular pathogenesis in the tuberous sclerosis complex.
    Print ISSN: 0964-6906
    Digitale ISSN: 1460-2083
    Thema: Biologie , Medizin
    Publiziert von Oxford University Press
    Standort Signatur Erwartet Verfügbarkeit
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  • 5
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    NLRP7 affects trophoblast lineage differentiation, binds to overexpressed YY1 and alters CpG methylation (2014)
    Oxford University Press
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    Publikationsdatum: 2014-01-11
    Beschreibung: Maternal-effect mutations in NLRP7 cause rare biparentally inherited hydatidiform moles (BiHMs), abnormal pregnancies containing hypertrophic vesicular trophoblast but no embryo. BiHM trophoblasts display abnormal DNA methylation patterns affecting maternally methylated germline differentially methylated regions (gDMRs), suggesting that NLRP7 plays an important role in reprogramming imprinted gDMRs. How NLRP7—a component of the CATERPILLAR family of proteins involved in innate immunity and apoptosis—causes these specific DNA methylation and trophoblast defects is unknown. Because rodents lack NLRP7, we used human embryonic stem cells to study its function and demonstrate that NLRP7 interacts with YY1, an important chromatin-binding factor. Reduced NLRP7 levels alter DNA methylation and accelerate trophoblast lineage differentiation. NLRP7 thus appears to function in chromatin reprogramming and DNA methylation in the germline or early embryonic development, functions not previously associated with members of the NLRP family.
    Print ISSN: 0964-6906
    Digitale ISSN: 1460-2083
    Thema: Biologie , Medizin
    Publiziert von Oxford University Press
    Standort Signatur Erwartet Verfügbarkeit
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  • 6
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    APP2: automatic tracing of 3D neuron morphology based on hierarchical pruning of a gray-weighted image distance-tree (2013)
    Oxford University Press
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    Publikationsdatum: 2013-05-23
    Beschreibung: Motivation: Tracing of neuron morphology is an essential technique in computational neuroscience. However, despite a number of existing methods, few open-source techniques are completely or sufficiently automated and at the same time are able to generate robust results for real 3D microscopy images. Results: We developed all-path-pruning 2.0 (APP2) for 3D neuron tracing. The most important idea is to prune an initial reconstruction tree of a neuron’s morphology using a long-segment-first hierarchical procedure instead of the original termini-first-search process in APP. To further enhance the robustness of APP2, we compute the distance transform of all image voxels directly for a gray-scale image, without the need to binarize the image before invoking the conventional distance transform. We also design a fast-marching algorithm-based method to compute the initial reconstruction trees without pre-computing a large graph. This method allows us to trace large images. We bench-tested APP2 on ~700 3D microscopic images and found that APP2 can generate more satisfactory results in most cases than several previous methods. Availability: The software has been implemented as an open-source Vaa3D plugin. The source code is available in the Vaa3D code repository http://vaa3d.org . Contact: hanchuanp@alleninstitute.org Supplementary information: Supplementary data are available at Bioinformatics online.
    Print ISSN: 1367-4803
    Digitale ISSN: 1460-2059
    Thema: Biologie , Informatik , Medizin
    Publiziert von Oxford University Press
    Standort Signatur Erwartet Verfügbarkeit
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  • 7
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    Characterization of p38 MAPK isoforms for drug resistance study using systems biology approach (2014)
    Oxford University Press
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    Publikationsdatum: 2014-06-27
    Beschreibung: Motivation: p38 mitogen-activated protein kinase activation plays an important role in resistance to chemotherapeutic cytotoxic drugs in treating multiple myeloma (MM). However, how the p38 mitogen-activated protein kinase signaling pathway is involved in drug resistance, in particular the roles that the various p38 isoforms play, remains largely unknown. Method: To explore the underlying mechanisms, we developed a novel systems biology approach by integrating liquid chromatography–mass spectrometry and reverse phase protein array data from human MM cell lines with computational pathway models in which the unknown parameters were inferred using a proposed novel algorithm called modularized factor graph. Results: New mechanisms predicted by our models suggest that combined activation of various p38 isoforms may result in drug resistance in MM via regulating the related pathways including extracellular signal-regulated kinase (ERK) pathway and NFB pathway. ERK pathway regulating cell growth is synergistically regulated by p38 isoform, whereas nuclear factor kappa B (NFB) pathway regulating cell apoptosis is synergistically regulated by p38α isoform. This finding that p38 isoform promotes the phosphorylation of ERK1/2 in MM cells treated with bortezomib was validated by western blotting. Based on the predicted mechanisms, we further screened drug combinations in silico and found that a promising drug combination targeting ERK1/2 and NFB might reduce the effects of drug resistance in MM cells. This study provides a framework of a systems biology approach to studying drug resistance and drug combination selection. Availability and implementation: RPPA experimental Data and Matlab source codes of modularized factor graph for parameter estimation are freely available online at http://ctsb.is.wfubmc.edu/publications/modularized-factor-graph.php Contact: xizhou@wakehealth.edu or zhanglcq@swu.edu.cn Supplementary information: Supplementary data are available at Bioinformatics online.
    Print ISSN: 1367-4803
    Digitale ISSN: 1460-2059
    Thema: Biologie , Informatik , Medizin
    Publiziert von Oxford University Press
    Standort Signatur Erwartet Verfügbarkeit
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  • 8
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    Automated cellular annotation for high-resolution images of adult Caenorhabditis elegans (2013)
    Oxford University Press
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    Publikationsdatum: 2013-06-24
    Beschreibung: Motivation: Advances in high-resolution microscopy have recently made possible the analysis of gene expression at the level of individual cells. The fixed lineage of cells in the adult worm Caenorhabditis elegans makes this organism an ideal model for studying complex biological processes like development and aging. However, annotating individual cells in images of adult C.elegans typically requires expertise and significant manual effort. Automation of this task is therefore critical to enabling high-resolution studies of a large number of genes. Results: In this article, we describe an automated method for annotating a subset of 154 cells (including various muscle, intestinal and hypodermal cells) in high-resolution images of adult C.elegans . We formulate the task of labeling cells within an image as a combinatorial optimization problem, where the goal is to minimize a scoring function that compares cells in a test input image with cells from a training atlas of manually annotated worms according to various spatial and morphological characteristics. We propose an approach for solving this problem based on reduction to minimum-cost maximum-flow and apply a cross-entropy–based learning algorithm to tune the weights of our scoring function. We achieve 84% median accuracy across a set of 154 cell labels in this highly variable system. These results demonstrate the feasibility of the automatic annotation of microscopy-based images in adult C.elegans . Contact: saerni@cs.stanford.edu
    Print ISSN: 1367-4803
    Digitale ISSN: 1460-2059
    Thema: Biologie , Informatik , Medizin
    Publiziert von Oxford University Press
    Standort Signatur Erwartet Verfügbarkeit
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  • 9
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    Association of P2X7R gene polymorphisms with systemic lupus erythematosus in a Chinese population (2013)
    Oxford University Press
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    Publikationsdatum: 2013-04-20
    Beschreibung: The P2X7 receptor is a ligand-gated cationic channel receptor that is actived by ATP and normally expressed by a variety of immune system cells, including macrophages and lymphocytes. Because it leads to release of IL-1β and cell death by apoptosis or necrosis, it is a potential therapeutic target for a variety of autoimmune inflammatory diseases, such as systemic lupus erythematosus (SLE). The P2X7R gene is highly polymorphic, and many single-nucleotide polymorphisms (SNPs) have been detected. A case–control study was performed to investigate the associations of SNPs in the P2X7R gene (rs1718119, rs2230911 and rs3751143) with susceptibility to SLE in 535 Chinese SLE patients and 532 controls. Results showed that rs1718119 was associated with SLE; in particular carriers of the A allele and AA/AG/(AG+AA) genotypes were at lower risk of the disease [A versus G, P 〈 0.001, odds ratio (OR) = 0.543, 95% CI: 0.424–0.697; AG versus GG, P = 0.018, OR = 0.659, 95% CI: 0.466–0.931; AA versus GG, P = 0.011, OR = 0.176, 95% CI: 0.046–0.668; AG+AA versus GG, P = 0.004, OR = 0.607, 95% CI: 0.433–0.850], but no significant differences in rs2230911 and rs3751143 were observed between SLE patients and controls. Stratification of cases for the presence of nephritis showed that rs2230911 G allele and CG/(CG+GG) genotypes were at a lower risk of SLE with nephritis (LN) (G versus C, P = 0.011, OR = 0.640, 95% CI: 0.454–0.903; CG versus CC, P = 0.035, OR = 0.645, 95% CI: 0.429–0.970; GG versus CC, P = 0.101, OR = 0.349, 95% CI: 0.099–1.228; CG+GG versus CC, P = 0.015 OR = 0.612, 95% CI: 0.411–0.910), but rs1718119 and rs3751143 were not associated with LN. Analysis of the haplotypes revealed one haplotype (ACA) that appeared to be a significantly ‘protective’ haplotype ( P = 0.009, OR = 0.708, 95% CI: 0.546–0.918) with SLE. The findings suggest that the P2X7R gene might contribute to SLE susceptibility in the Chinese population.
    Print ISSN: 0267-8357
    Digitale ISSN: 1464-3804
    Thema: Biologie , Medizin
    Publiziert von Oxford University Press
    Standort Signatur Erwartet Verfügbarkeit
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  • 10
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    Dimension reduction and predictor selection in semiparametric models (2013)
    Oxford University Press
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    Publikationsdatum: 2013-08-12
    Beschreibung: Dimension reduction in semiparametric regressions includes construction of informative linear combinations and selection of contributing predictors. To reduce the predictor dimension in semiparametric regressions, we propose an 1 -minimization of sliced inverse regression with the Dantzig selector, and establish a non-asymptotic error bound for the resulting estimator. We also generalize the regularization concept to sliced inverse regression with an adaptive Dantzig selector. This ensures that all contributing predictors are selected with high probability, and that the resulting estimator is asymptotically normal even when the predictor dimension diverges to infinity. Numerical studies confirm our theoretical observations and demonstrate that our proposals are superior to existing estimators in terms of both dimension reduction and predictor selection.
    Print ISSN: 0006-3444
    Digitale ISSN: 1464-3510
    Thema: Biologie , Mathematik , Medizin
    Publiziert von Oxford University Press
    Standort Signatur Erwartet Verfügbarkeit
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