The iceLogo web server and SOAP service for determining protein consensus sequences

he iceLogo web server and SOAP service implement the previously published iceLogo algorithm. iceLogo builds on probability theory to visualize protein consensus sequences in a format resembling sequence logos. Peptide sequences are compared against a reference sequence set that can be tailored to the studied system and the used protocol. As such, not only over-but also underrepresented residues can be visualized in a statistically sound manner, which further allows the user to easily analyse and interpret conserved sequence patterns in proteins. The web application and SOAP service can be found free and open to all users without the need for a login on http://iomics.ugent.be/icelogoserver/main.html

Opinion formation driven by PageRank node influence on directed networks

We study a two states opinion formation model driven by PageRank node influence and report an extensive numerical study on how PageRank affects collective opinion formations in large-scale empirical directed networks. In our model the opinion of a node can be updated by the sum of its neighbor nodes' opinions weighted by the node influence of the neighbor nodes at each step. We consider PageRank probability and its sublinear power as node influence measures and investigate evolution of opinion under various conditions. First, we observe that all networks reach steady state opinion after a certain relaxation time. This time scale is decreasing with the heterogeneity of node influence in the networks. Second, we find that our model shows consensus and non-consensus behavior in steady state depending on types of networks: Web graph, citation network of physics articles, and LiveJournal social network show non-consensus behavior while Wikipedia article network shows consensus behavior. Third, we find that a more heterogeneous influence distribution leads to a more uniform opinion state in the cases of Web graph, Wikipedia, and Livejournal. However, the opposite behavior is observed in the citation network. Finally we identify that a small number of influential nodes can impose their own opinion on significant fraction of other nodes in all considered networks. Our study shows that the effects of heterogeneity of node influence on opinion formation can be significant and suggests further investigations on the interplay between node influence and collective opinion in networks.Comment: 10 pages, 6 figures. Published in Physica A 436, 707-715 (2015

A community based approach for managing ontology alignments

The Semantic Web is rapidly becoming a defacto distributed repository for semantically represented data, thus leveraging on the added on value of the network effect. Various ontology mapping techniques and tools have been devised to facilitate the bridging and integration of distributed data repositories. Nevertheless, ontology mapping can benefitfrom human supervision to increase accuracy of results. The spread of Web 2.0 approaches demonstrate the possibility of using collaborative techniques for reaching consensus. While a number of prototypes for collaborative ontology construction are being developed, collaborative ontology mapping is not yet well investigated. In this paper, we describe a prototype that combines off-the-shelf ontology mapping tools with social software techniques to enable users to collaborate on mapping ontologies

Electronic Resources and Heterodox Economists

The idea of measuring scientific relevance by counting citations is gaining ever-growing consensus among economists, and thanks to the electronic bibliographic resources now available the procedure has become relatively simple and fast. However, when it comes to putting the idea into practice many challenging problems emerge. This paper uses five of the principal bibliographic electronic resources (EconLit, JSTOR, Web of Science, Scopus and Google Scholar) to test the practical applicability of this method for measuring relevance to the particular case of heterodox economics.heterodox economists; EconLit; JSTOR; Web of Science; Scopus; Google Scholar

Helping patients discuss CINV management : development of a patient charter

In April 2012, an Expert Group of specialist cancer nurses working in a variety of settings (e.g. chemotherapy delivery, chemotherapy service design, research, nurse leadership and patient information/advocacy) participated in telephone/web-based meetings, with the aim of sharing current experience of chemotherapy-induced nausea and vomiting (CINV) management, and reaching a consensus on the development of a Patient Charter, designed to help patients understand CINV management, and setting out key questions they may wish to ask their healthcare professionals

Integrative analysis of large-scale biological data sets

We present two novel web-applications for microarray and gene/protein set analysis, ArrayMining.net and TopoGSA. These bioinformatics tools use integrative analysis methods, including ensemble and consensus machine learning techniques, as well as modular combinations of different analysis types, to extract new biological insights from experimental transcriptomics and proteomics data. They enable researchers to combine related algorithms and datasets to increase the robustness and accuracy of statistical analyses and exploit synergies of different computational methods, ranging from statistical learning to optimization and topological network analysis