Proteomics research routinely involves identifying peptides and proteins via tandem mass spectrometry sequence database search. Thus the database search engine is an integral tool in many proteomics research groups. Here, we introduce the Comet search engine to the existing landscape of commercial and open source database search tools. Comet is open source, freely available, and based on one of the original sequence database search tools that has been widely used for many years.
Using the conceptual framework of shared decision-making and evidence-based practice, a web portal was developed to serve as a generic (non disease-specific) tailored intervention to improve the lay public’s health literacy skills.
The MSIS-29 was developed to assess the physical and psychological impact of MS. The aims of this study were to use the responses to the MSIS-29 via the web portal of the UK MS Register to: examine the internal properties of the scale delivered via the internet, profile the cohort, and assess how well the scale measures impact of disability on the potential workforce.
Ondex Web is a new web-based implementation of the network visualization and exploration tools from the Ondex data integration platform. New features such as context-sensitive menus and annotation tools provide users with intuitive ways to explore and manipulate the appearance of heterogeneous biological networks. Ondex Web is open source, written in Java and can be easily embedded into web sites as an applet. Ondex Web supports loading data from a variety of network formats, such as XGMML, NWB, Pajek and OXL.
The EQ-5D is a widely-used, standardised, quality of life measure producing health profiles, indices and states. The aims of this study were to assess the role of various factors in how people with Multiple Sclerosis rate their quality of life, based on responses to the EQ-5D received via the web portal of the UK MS Register.
Contrary to the assumption that web browsers are designed to support the user, an examination of a 900,000 distinct PCs shows that web browsers comprise a complex ecosystem with millions of addons collaborating and competing with each other. It is possible for addons to “sneak in” through third party installations or to get “kicked out” by their competitors without user involvement. This study examines that ecosystem quantitatively by constructing a large-scale graph with nodes corresponding to users, addons, and words (terms) that describe addon functionality. Analyzing addon interactions at user level using the Personalized PageRank (PPR) random walk measure shows that the graph demonstrates ecological resilience. Adapting the PPR model to analyzing the browser ecosystem at the level of addon manufacturer, the study shows that some addon companies are in symbiosis and others clash with each other as shown by analyzing the behavior of 18 prominent addon manufacturers. Results may herald insight on how other evolving internet ecosystems may behave, and suggest a methodology for measuring this behavior. Specifically, applying such a methodology could transform the addon market.