A measurement-based approach to service modeling and bandwidth estimation in IEEE 802.11 wireless networks

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Understanding Fairness and its Impact on Quality of Service in IEEE 802.11

The Distributed Coordination Function (DCF) aims at fair and efficient medium access in IEEE 802.11. In face of its success, it is remarkable that there is little consensus on the actual degree of fairness achieved, particularly bearing its impact on quality of service in mind. In this paper we provide an accurate model for the fairness of the DCF. Given M greedy stations we assume fairness if a tagged station contributes a share of 1/M to the overall number of packets transmitted. We derive the probability distribution of fairness deviations and support our analytical results by an extensive set of measurements. We find a closed-form expression for the improvement of long-term over short-term fairness. Regarding the random countdown values we quantify the significance of their distribution whereas we discover that fairness is largely insensitive to the distribution parameters. Based on our findings we view the DCF as emulating an ideal fair queuing system to quantify the deviations from a fair rate allocation. We deduce a stochastic service curve model for the DCF to predict packet delays in IEEE 802.11. We show how a station can estimate its fair bandwidth share from passive measurements of its traffic arrivals and departures

Interoperability Between GRDC\u27s Data Holding And The GEOSS Infrastructure

The Global Runoff Data Centre (GRDC) operates under the auspices of the World Meteorological Organization as an international data centre for hydrological data and information on a global scale. Its primary objective is to support the water and climate related programmes and projects of the United Nations, its specialised agencies, and the scientific research community on global and climate change and integrated water resources management. The Global Runoff Database maintained by the GRDC is a valuable data resource and a subset of its data is contributed to the Global Earth Observation System of Systems’ (GEOSS) freely accessible Data Core. As a partner in the project GEOSS Interoperability for Weather, Ocean and Water (GEOWOW) the GRDC supports the evolving GEOSS in terms of interoperability, standardization and functionality. In the framework of GEOWOW a profile of the OGC Sensor Observation Service Interface Standard 2.0 (SOS) is being developed. This SOS Profile for the Hydrology Domain specifies extensions to the service interface and uses the OGC WaterML 2.0 standard for encoding hydrological time series data. Moreover, technical partners of the GEOWOW project facilitate software implementations of the standardization advancements. Deploying and incorporating these into GRDC’s data holding infrastructure allows for a seamless integration of GRDC’s data provision capabilities into GEOSS. Furthermore, client web applications to visualize time series data provided via an OGC Web Service infrastructure makes it possible to offer additional benefit and allows for accessing and assessing data more easily

CDCOCA: a statistical method to define complexity dependent co-occurring chromosomal aberrations

<p>Abstract</p> <p>Background</p> <p>Copy number alterations (CNA) play a key role in cancer development and progression. Since more than one CNA can be detected in most tumors, frequently co-occurring genetic CNA may point to cooperating cancer related genes. Existing methods for co-occurrence evaluation so far have not considered the overall heterogeneity of CNA per tumor, resulting in a preferential detection of frequent changes with limited specificity for each association due to the high genetic instability of many samples.</p> <p>Method</p> <p>We hypothesize that in cancer some linkage-independent CNA may display a non-random co-occurrence, and that these CNA could be of pathogenetic relevance for the respective cancer. We also hypothesize that the statistical relevance of co-occurring CNA may depend on the sample specific CNA complexity. We verify our hypotheses with a simulation based algorithm CDCOCA (complexity dependence of co-occurring chromosomal aberrations).</p> <p>Results</p> <p>Application of CDCOCA to example data sets identified co-occurring CNA from low complex background which otherwise went unnoticed. Identification of cancer associated genes in these co-occurring changes can provide insights of cooperative genes involved in oncogenesis.</p> <p>Conclusions</p> <p>We have developed a method to detect associations of regional copy number abnormalities in cancer data. Along with finding statistically relevant CNA co-occurrences, our algorithm points towards a generally low specificity for co-occurrence of regional imbalances in CNA rich samples, which may have negative impact on pathway modeling approaches relying on frequent CNA events.</p

miRNA Expression Profiling in Migrating Glioblastoma Cells: Regulation of Cell Migration and Invasion by miR-23b via Targeting of Pyk2

Glioblastoma (GB) is the most common and lethal type of primary brain tumor. Clinical outcome remains poor and is essentially palliative due to the highly invasive nature of the disease. A more thorough understanding of the molecular mechanisms that drive glioma invasion is required to limit dispersion of malignant glioma cells.We investigated the potential role of differential expression of microRNAs (miRNA) in glioma invasion by comparing the matched large-scale, genome-wide miRNA expression profiles of migrating and migration-restricted human glioma cells. Migratory and migration-restricted cell populations from seven glioma cell lines were isolated and profiled for miRNA expression. Statistical analyses revealed a set of miRNAs common to all seven glioma cell lines that were significantly down regulated in the migrating cell population relative to cells in the migration-restricted population. Among the down-regulated miRNAs, miR-23b has been reported to target potential drivers of cell migration and invasion in other cell types. Over-expression of miR-23b significantly inhibited glioma cell migration and invasion. A bioinformatics search revealed a conserved target site within the 3' untranslated region (UTR) of Pyk2, a non-receptor tyrosine kinase previously implicated in the regulation of glioma cell migration and invasion. Increased expression of miR-23b reduced the protein expression level of Pyk2 in glioma cells but did not significantly alter the protein expression level of the related focal adhesion kinase FAK. Expression of Pyk2 via a transcript variant missing the 3'UTR in miR-23b-expressing cells partially rescued cell migration, whereas expression of Pyk2 via a transcript containing an intact 3'UTR failed to rescue cell migration.Reduced expression of miR-23b enhances glioma cell migration in vitro and invasion ex vivo via modulation of Pyk2 protein expression. The data suggest that specific miRNAs may regulate glioma migration and invasion to influence the progression of this disease

The Accuracy of Survival Time Prediction for Patients with Glioma Is Improved by Measuring Mitotic Spindle Checkpoint Gene Expression

Identification of gene expression changes that improve prediction of survival time across all glioma grades would be clinically useful. Four Affymetrix GeneChip datasets from the literature, containing data from 771 glioma samples representing all WHO grades and eight normal brain samples, were used in an ANOVA model to screen for transcript changes that correlated with grade. Observations were confirmed and extended using qPCR assays on RNA derived from 38 additional glioma samples and eight normal samples for which survival data were available. RNA levels of eight major mitotic spindle assembly checkpoint (SAC) genes (BUB1, BUB1B, BUB3, CENPE, MAD1L1, MAD2L1, CDC20, TTK) significantly correlated with glioma grade and six also significantly correlated with survival time. In particular, the level of BUB1B expression was highly correlated with survival time (p<0.0001), and significantly outperformed all other measured parameters, including two standards; WHO grade and MIB-1 (Ki-67) labeling index. Measurement of the expression levels of a small set of SAC genes may complement histological grade and other clinical parameters for predicting survival time

Mutational Analysis of EGFR and Related Signaling Pathway Genes in Lung Adenocarcinomas Identifies a Novel Somatic Kinase Domain Mutation in FGFR4

BACKGROUND: Fifty percent of lung adenocarcinomas harbor somatic mutations in six genes that encode proteins in the EGFR signaling pathway, i.e., EGFR, HER2/ERBB2, HER4/ERBB4, PIK3CA, BRAF, and KRAS. We performed mutational profiling of a large cohort of lung adenocarcinomas to uncover other potential somatic mutations in genes of this signaling pathway that could contribute to lung tumorigenesis. METHODOLOGY/PRINCIPAL FINDINGS: We analyzed genomic DNA from a total of 261 resected, clinically annotated non-small cell lung cancer (NSCLC) specimens. The coding sequences of 39 genes were screened for somatic mutations via high-throughput dideoxynucleotide sequencing of PCR-amplified gene products. Mutations were considered to be somatic only if they were found in an independent tumor-derived PCR product but not in matched normal tissue. Sequencing of 9MB of tumor sequence identified 239 putative genetic variants. We further examined 22 variants found in RAS family genes and 135 variants localized to exons encoding the kinase domain of respective proteins. We identified a total of 37 non-synonymous somatic mutations; 36 were found collectively in EGFR, KRAS, BRAF, and PIK3CA. One somatic mutation was a previously unreported mutation in the kinase domain (exon 16) of FGFR4 (Glu681Lys), identified in 1 of 158 tumors. The FGFR4 mutation is analogous to a reported tumor-specific somatic mutation in ERBB2 and is located in the same exon as a previously reported kinase domain mutation in FGFR4 (Pro712Thr) in a lung adenocarcinoma cell line. CONCLUSIONS/SIGNIFICANCE: This study is one of the first comprehensive mutational analyses of major genes in a specific signaling pathway in a sizeable cohort of lung adenocarcinomas. Our results suggest the majority of gain-of-function mutations within kinase genes in the EGFR signaling pathway have already been identified. Our findings also implicate FGFR4 in the pathogenesis of a subset of lung adenocarcinomas

Copy Number Analysis Identifies Novel Interactions Between Genomic Loci in Ovarian Cancer

Ovarian cancer is a heterogeneous disease displaying complex genomic alterations, and consequently, it has been difficult to determine the most relevant copy number alterations with the scale of studies to date. We obtained genome-wide copy number alteration (CNA) data from four different SNP array platforms, with a final data set of 398 ovarian tumours, mostly of the serous histological subtype. Frequent CNA aberrations targeted many thousands of genes. However, high-level amplicons and homozygous deletions enabled filtering of this list to the most relevant. The large data set enabled refinement of minimal regions and identification of rare amplicons such as at 1p34 and 20q11. We performed a novel co-occurrence analysis to assess cooperation and exclusivity of CNAs and analysed their relationship to patient outcome. Positive associations were identified between gains on 19 and 20q, gain of 20q and loss of X, and between several regions of loss, particularly 17q. We found weak correlations of CNA at genomic loci such as 19q12 with clinical outcome. We also assessed genomic instability measures and found a correlation of the number of higher amplitude gains with poorer overall survival. By assembling the largest collection of ovarian copy number data to date, we have been able to identify the most frequent aberrations and their interactions