Gene set analysis of differential expression, which identifies collectively differentially expressed gene sets, has become an important tool for biology. The power of this approach lies in its reduction of the dimensionality of the statistical problem and its incorporation of biological interpretation by construction. Many approaches to gene set analysis have been proposed, but benchmarking their performance in the setting of real biological data is difficult due to the lack of a gold standard. In a previously published work we proposed a geometrical approach to differential expression which performed highly in benchmarking tests and compared well to the most popular methods of differential gene expression. As reported, this approach has a natural extension to gene set analysis which we call Principal Angle Enrichment Analysis (PAEA). PAEA employs dimensionality reduction and a multivariate approach for gene set enrichment analysis. However, the performance of this method has not been assessed nor its implementation as a web-based tool. Here we describe new benchmarking protocols for gene set analysis methods and find that PAEA performs highly. The PAEA method is implemented as a user-friendly web-based tool, which contains 70 gene set libraries and is freely available to the community.

MOTIVATION: Identification of differentially expressed genes is an important step in extracting knowledge from gene expression profiling studies. The raw expression data from microarray and other high-throughput technologies is deposited into the Gene Expression Omnibus (GEO) and served as Simple Omnibus Format in Text (SOFT) files. However, to extract and analyze differentially expressed genes from GEO requires significant computational skills. RESULTS: Here we introduce GEO2Enrichr, a browser extension for extracting differentially expressed gene sets from GEO and analyzing those sets with Enrichr, an independent gene set enrichment analysis tool containing over 70 000 annotated gene sets organized into 75 gene-set libraries. GEO2Enrichr adds JavaScript code to GEO web-pages; this code scrapes user selected accession numbers and metadata, and then, with one click, users can submit this information to a web-server application that downloads the SOFT files, parses, cleans and normalizes the data, identifies the differentially expressed genes, and then pipes the resulting gene lists to Enrichr for downstream functional analysis. GEO2Enrichr opens a new avenue for adding functionality to major bioinformatics resources such GEO by integrating tools and resources without the need for a plug-in architecture. Importantly, GEO2Enrichr helps researchers to quickly explore hypotheses with little technical overhead, lowering the barrier of entry for biologists by automating data processing steps needed for knowledge extraction from the major repository GEO. AVAILABILITY AND IMPLEMENTATION: GEO2Enrichr is an open source tool, freely available for installation as browser extensions at the Chrome Web Store and FireFox Add-ons. Documentation and a browser independent web application can be found at http://amp.pharm.mssm.edu/g2e/. CONTACT: [email protected].

Offshore software development has been identified as one of the most striking manifestations of contemporary globalisation and as evidence of placelessness, the idea that information and communication technologies have rendered location irrelevant. Research in the International Business and Information Systems fields, in contrast, has suggested that all locations are not equal and has identified a number of characteristics that may influence the attractiveness of a location for multinational investment and offshoring, respectively. These literatures, however, focus almost exclusively on quantitative, economic characteristics that are seen as fixed and applying uniformly throughout a whole country. They therefore offer little guidance on the suitability of particular locations as offshoring destinations, especially in countries without a track record in offshore software development. Drawing on two cases of nearshore software development centres set up by offshore service providers in the Caribbean, this paper illustrates that, while the initial decision to establish the ventures reflected a logic of placelessness, characteristics of these particular locations affected their subsequent success. Through the findings, we therefore develop a typology of espoused, unanticipated and remediable locational characteristics, which illustrates that locational attractiveness may vary significantly within countries and that offshore service providers and government agencies can modify locational characteristics to their advantage.

Article Free Access Share on The long and winding road: collaborative IT and organisational change Authors: Helena Karsten University of Jyväskylä Department of Computer Science and Information Systems, P.O. Box 35, 40351 Jyväskylä Finland University of Jyväskylä Department of Computer Science and Information Systems, P.O. Box 35, 40351 Jyväskylä FinlandView Profile , Matthew Jones University of Cambridge, The Judge Institite of Management Studies, Trumpington Street, Cambridge CB2 1AG, United Kingdom University of Cambridge, The Judge Institite of Management Studies, Trumpington Street, Cambridge CB2 1AG, United KingdomView Profile Authors Info & Claims CSCW '98: Proceedings of the 1998 ACM conference on Computer supported cooperative workNovember 1998 Pages 29–38https://doi.org/10.1145/289444.289456Published:01 November 1998Publication History 20citation1,447DownloadsMetricsTotal Citations20Total Downloads1,447Last 12 Months37Last 6 weeks2 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF

In the past, the use of computer models in decision support has involved the interpretation of written reports derived from the output of the model. In recent years, however, the development of micro-computers and istributed computing systems has made it possible for decision-makers to be provided, not with a written report, but with a copy of the model itself. The new relationship between the user and the model, which this development establishes, has important implications for the way in which decision support systems (DSSs) are designed and used.