A Feasibility Study of Automated Support for Similarity Analysis of Natural Language Requirements in Market-Driven Development

In market-driven software development there is a strong need for support to handle congestion in the requirements engineering process, which may occur as the demand for short time-to-market is combined with a rapid arrival of new requirements from many different sources. Automated analysis of the continuous flow of incoming requirements provides an opportunity to increase the efficiency of the requirements engineering process. This paper presents empirical evaluations of the benefit of automated similarity analysis of textual requirements, where existing information retrieval techniques are used to statistically measure requirements similarity. The results show that automated analysis of similarity among textual requirements is a promising technique that may provide effective support in identifying relationships between requirements

Treatment trends in allergic rhinitis and asthma: a British ENT survey

<p>Abstract</p> <p>Background</p> <p>Allergic Rhinitis is a common Ear, Nose and Throat disorder. Asthma and Allergic Rhinitis are diseases with similar underlying mechanism and pathogenesis. The aim of this survey was to highlight current treatment trends for Allergic Rhinitis and Asthma.</p> <p>Method</p> <p>A questionnaire was emailed to all registered consultant members of the British Association of Otorhinolaryngologists - Head and Neck Surgeons regarding the management of patients with Allergic Rhinitis and related disorders.</p> <p>Results</p> <p>Survey response rate was 56%. The results indicate a various approach in the investigation and management of Allergic Rhinitis compatible with recommendations from the Allergic Rhinitis and Its Impact on Asthma guidelines in collaboration with the World Health Organisation.</p> <p>Conclusion</p> <p>A combined management approach for patients with Allergic Rhinitis and concomitant Asthma may reduce medical treatment costs for these conditions and improve symptom control and quality of life.</p

Second Generation of Antisense Oligonucleotides: From Nuclease Resistance to Biological Efficacy in Animals

From efforts to improve the biophysical properties of antisense oligonucleotides by incorporating backbone- or sugar-modified nucleoside analogs, 2'-O-methoxyethyl ribonucleosides 8b were identified as building blocks for a second generation of antisense oligonucleotides. Compounds containing these modifications were demonstrated to combine the benefit of a high binding affinity to the RNA complement with a large increase in nuclease resistance, allowing the use of regular phosphodiester linkages. Chimeric oligonucleotides with 2'-O-methoxyethyl ribonucleosides, 8b, in the wings and a central DNA-phosphorothioate window were shown to efficiently downregulate C-'raf' kinase and PKC-α messenger-RNA in tumor cell lines resulting in a profound inhibition of cell proliferation. The same compounds were able to effectively reduce the growth of tumors in animal models at low concentrations indicating the potential utility of these second generation antisense oligonucleotides for therapeutic applications

Discovering cancer genes by integrating network and functional properties

<p>Abstract</p> <p>Background</p> <p>Identification of novel cancer-causing genes is one of the main goals in cancer research. The rapid accumulation of genome-wide protein-protein interaction (PPI) data in humans has provided a new basis for studying the topological features of cancer genes in cellular networks. It is important to integrate multiple genomic data sources, including PPI networks, protein domains and Gene Ontology (GO) annotations, to facilitate the identification of cancer genes.</p> <p>Methods</p> <p>Topological features of the PPI network, as well as protein domain compositions, enrichment of gene ontology categories, sequence and evolutionary conservation features were extracted and compared between cancer genes and other genes. The predictive power of various classifiers for identification of cancer genes was evaluated by cross validation. Experimental validation of a subset of the prediction results was conducted using siRNA knockdown and viability assays in human colon cancer cell line DLD-1.</p> <p>Results</p> <p>Cross validation demonstrated advantageous performance of classifiers based on support vector machines (SVMs) with the inclusion of the topological features from the PPI network, protein domain compositions and GO annotations. We then applied the trained SVM classifier to human genes to prioritize putative cancer genes. siRNA knock-down of several SVM predicted cancer genes displayed greatly reduced cell viability in human colon cancer cell line DLD-1.</p> <p>Conclusion</p> <p>Topological features of PPI networks, protein domain compositions and GO annotations are good predictors of cancer genes. The SVM classifier integrates multiple features and as such is useful for prioritizing candidate cancer genes for experimental validations.</p