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- You, Lei, et al.
(författare)
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Cross-layer optimization of wireless multihop networks with one-hop two-way network coding
- 2011
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Ingår i: Computer Networks. - : Elsevier BV. - 1389-1286 .- 1872-7069. ; 55:8, s. 1747-1769
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Tidskriftsartikel (refereegranskat)abstract
- In this paper, we investigate optimal cross-layer design of congestion control, routing, one-hop two-way inter-commodity (OTIC) network coding and scheduling in wireless multihop networks utilizing the broadcast advantage of wireless medium. We first present an achievable rate region with OTIC network coding by introducing virtual flow rates in a node. Then we formulate the network utility maximization problem subject to constraints on this achievable rate region, and analyze the complexities of both node- and path-based formulation with no network coding, OTIC network coding, and overhearing network coding. After that, we solve it using dual decomposition and subgradient method. Based on the solution, we present a new queue model, which is able to facilitate the coding operation between two-way commodities, and then propose a backpressure-based cross-layer optimization algorithm with low coding complexity and overhead. Afterwards, we analyze the stability and asymptotical optimality of the proposed cross-layer algorithm by Lyapunov drift technique, and evaluate its performance through extensive simulation. By comparing with the pure routing scheme under both primary and two-hop interference models in an illustrative topology, it is shown that with the proposed joint optimization algorithms, the OTIC network coding can interact adaptively and optimally with other components in different layers and achieve high throughput gain. Simulation of the proposed algorithm in a mesh network with base station and a random ad hoc network justifies that OTIC network coding can obtain considerable throughput gain with low complexity in various kinds of networks.
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- Lawrenson, Kate, et al.
(författare)
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Functional mechanisms underlying pleiotropic risk alleles at the 19p13.1 breast-ovarian cancer susceptibility locus
- 2016
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Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 7
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Tidskriftsartikel (refereegranskat)abstract
- A locus at 19p13 is associated with breast cancer (BC) and ovarian cancer (OC) risk. Here we analyse 438 SNPs in this region in 46,451 BC and 15,438 OC cases, 15,252 BRCA1 mutation carriers and 73,444 controls and identify 13 candidate causal SNPs associated with serous OC (P=9.2 × 10-20), ER-negative BC (P=1.1 × 10-13), BRCA1-associated BC (P=7.7 × 10-16) and triple negative BC (P-diff=2 × 10-5). Genotype-gene expression associations are identified for candidate target genes ANKLE1 (P=2 × 10-3) and ABHD8 (P<2 × 10-3). Chromosome conformation capture identifies interactions between four candidate SNPs and ABHD8, and luciferase assays indicate six risk alleles increased transactivation of the ADHD8 promoter. Targeted deletion of a region containing risk SNP rs56069439 in a putative enhancer induces ANKLE1 downregulation; and mRNA stability assays indicate functional effects for an ANKLE1 3′-UTR SNP. Altogether, these data suggest that multiple SNPs at 19p13 regulate ABHD8 and perhaps ANKLE1 expression, and indicate common mechanisms underlying breast and ovarian cancer risk.
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- Lu, Yingchang, et al.
(författare)
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A Transcriptome-Wide Association Study Among 97,898 Women to Identify Candidate Susceptibility Genes for Epithelial Ovarian Cancer Risk.
- 2018
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Ingår i: Cancer Research. - 0008-5472 .- 1538-7445. ; 78:18, s. 5419-5430
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Tidskriftsartikel (refereegranskat)abstract
- .AbstractLarge-scale genome-wide association studies (GWAS) have identified approximately 35 loci associated with epithelial ovarian cancer (EOC) risk. The majority of GWAS-identified disease susceptibility variants are located in noncoding regions, and causal genes underlying these associations remain largely unknown. Here, we performed a transcriptome-wide association study to search for novel genetic loci and plausible causal genes at known GWAS loci. We used RNA sequencing data (68 normal ovarian tissue samples from 68 individuals and 6,124 cross-tissue samples from 369 individuals) and high-density genotyping data from European descendants of the Genotype-Tissue Expression (GTEx V6) project to build ovarian and cross-tissue models of genetically regulated expression using elastic net methods. We evaluated 17,121 genes for their cis-predicted gene expression in relation to EOC risk using summary statistics data from GWAS of 97,898 women, including 29,396 EOC cases. With a Bonferroni-corrected significance level of P < 2.2 × 10−6, we identified 35 genes, including FZD4 at 11q14.2 (Z = 5.08, P = 3.83 × 10−7, the cross-tissue model; 1 Mb away from any GWAS-identified EOC risk variant), a potential novel locus for EOC risk. All other 34 significantly associated genes were located within 1 Mb of known GWAS-identified loci, including 23 genes at 6 loci not previously linked to EOC risk. Upon conditioning on nearby known EOC GWAS-identified variants, the associations for 31 genes disappeared and three genes remained (P < 1.47 × 10−3). These data identify one novel locus (FZD4) and 34 genes at 13 known EOC risk loci associated with EOC risk, providing new insights into EOC carcinogenesis.Significance: Transcriptomic analysis of a large cohort confirms earlier GWAS loci and reveals FZD4 as a novel locus associated with EOC risk. Cancer Res; 78(18); 5419–30. ©2018 AACR.
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