Vassiliki Gkantouna

Microattribution and nanopublication as means to incentivize the placement of human genome variation data into the public domain

The advances in bioinformatics required to annotate human genomic variants and to place them in public data repositories have not kept pace with their discovery. Moreover, a law of diminishing returns has begun to operate both in terms of data publication and submission. Although the continued deposition of such data in the public domain is essential to maximize both their scientific and clinical utility, rewards for data sharing are few, representing a serious practical impediment to data submission. To date, two main strategies have been adopted as a means to encourage the submission of human genomic variant data: (1) database journal linkups involving the affiliation of a scientific journal with a publicly available database and (2) microattribution, involving the unambiguous linkage of data to their contributors via a unique identifier. The latter could in principle lead to the establishment of a microcitation‐tracking system that acknowledges individual endeavor and achievement. Both approaches could incentivize potential data contributors, thereby encouraging them to share their data with the scientific community. Here, we summarize and critically evaluate approaches that have been proposed to address current deficiencies in data attribution and discuss ways in which they could become more widely adopted as novel scientific publication modalities. Hum Mutat 33:1503–1512, 2012.

Population-specific documentation of pharmacogenomic markers and their allelic frequencies in FINDbase

AIMS Population and ethnic group-specific allele frequencies of pharmacogenomic markers are poorly documented and not systematically collected in structured data repositories. We developed the Frequency of Inherited Disorders Pharmacogenomics database (FINDbase-PGx), a separate module of the FINDbase, aiming to systematically document pharmacogenomic allele frequencies in various populations and ethnic groups worldwide. MATERIALS & METHODS We critically collected and curated 214 scientific articles reporting pharmacogenomic markers allele frequencies in various populations and ethnic groups worldwide. Subsequently, in order to host the curated data, support data visualization and data mining, we developed a website application, utilizing Microsoft™ PivotViewer software. RESULTS Curated allelic frequency data pertaining to 144 pharmacogenomic markers across 14 genes, representing approximately 87,000 individuals from 150 populations worldwide, are currently included in FINDbase-PGx. A user-friendly query interface allows for easy data querying, based on numerous content criteria, such as population, ethnic group, geographical region, gene, drug and rare allele frequency. CONCLUSION FINDbase-PGx is a comprehensive database, which, unlike other pharmacogenomic knowledgebases, fulfills the much needed requirement to systematically document pharmacogenomic allelic frequencies in various populations and ethnic groups worldwide.

Developments in FINDbase worldwide database for clinically relevant genomic variation allele frequencies

FINDbase (http://www.findbase.org) aims to document frequencies of clinically relevant genomic variations, namely causative mutations and pharmacogenomic markers, worldwide. Each database record includes the population, ethnic group or geographical region, the disorder name and the related gene, accompanied by links to any related databases and the genetic variation together with its frequency in that population. Here, we report, in addition to the regular data content updates, significant developments in FINDbase, related to data visualization and querying, data submission, interrelation with other resources and a new module for genetic disease summaries. In particular, (i) we have developed new data visualization tools that facilitate data querying and comparison among different populations, (ii) we have generated a new FINDbase module, built around Microsoft’s PivotViewer (http://www.getpivot.com) software, based on Microsoft Silverlight technology (http://www.silverlight.net), that includes 259 genetic disease summaries from five populations, systematically collected from the literature representing the documented genetic makeup of these populations and (iii) the implementation of a generic data submission tool for every module currently available in FINDbase.

ETHNOS: A versatile electronic tool for the development and curation of national genetic databases

National and ethnic mutation databases (NEMDBs) are emerging online repositories, recording extensive information about the described genetic heterogeneity of an ethnic group or population. These resources facilitate the provision of genetic services and provide a comprehensive list of genomic variations among different populations. As such, they enhance awareness of the various genetic disorders. Here, we describe the features of the ETHNOS software, a simple but versatile tool based on a flat-file database that is specifically designed for the development and curation of NEMDBs. ETHNOS is a freely available software which runs more than half of the NEMDBs currently available. Given the emerging need for NEMDB in genetic testing services and the fact that ETHNOS is the only off-the-shelf software available for NEMDB development and curation, its adoption in subsequent NEMDB development would contribute towards data content uniformity, unlike the diverse contents and quality of the available gene (locus)-specific databases. Finally, we allude to the potential applications of NEMDBs, not only as worldwide central allele frequency repositories, but also, and most importantly, as data warehouses of individual-level genomic data, hence allowing for a comprehensive ethnicity-specific documentation of genomic variation.

FINDbase: a worldwide database for genetic variation allele frequencies updated

Frequency of INherited Disorders database (FIND base; http://www.findbase.org) records frequencies of causative genetic variations worldwide. Database records include the population and ethnic group or geographical region, the disorder name and the related gene, accompanied by links to any related external resources and the genetic variation together with its frequency in that population. In addition to the regular data content updates, we report the following significant advances: (i) the systematic collection and thorough documentation of population/ethnic group-specific pharmacogenomic markers allele frequencies for 144 markers in 14 genes of pharmacogenomic interest from different classes of drug-metabolizing enzymes and transporters, representing 150 populations and ethnic groups worldwide; (ii) the development of new data querying and visualization tools in the expanded FINDbase data collection, built around Microsoft’s PivotViewer software (http://www.getpivot.com), based on Microsoft Silverlight technology (http://www.silverlight.net) that facilitates querying of large data sets and visualizing the results; and (iii) the establishment of the first database journal, by affiliating FINDbase with Human Genomics and Proteomics, a new open-access scientific journal, which would serve as a prime example of a non-profit model for sustainable database funding.

Population-ethnic group specific genome variation allele frequency data: a querying and visualization journey.

National/ethnic mutation databases aim to document the genetic heterogeneity in various populations and ethnic groups worldwide. We have previously reported the development and upgrade of FINDbase (www.findbase.org), a database recording causative mutations and pharmacogenomic marker allele frequencies in various populations around the globe. Although this database has recently been upgraded, we continuously try to enhance its functionality by providing more advanced visualization tools that would further assist effective data querying and comparisons. We are currently experimenting in various visualization techniques on the existing FINDbase causative mutation data collection aiming to provide a dynamic research tool for the worldwide scientific community. We have developed an interactive web-based application for population-based mutation data retrieval. It supports sophisticated data exploration allowing users to apply advanced filtering criteria upon a set of multiple views of the underlying data collection and enables browsing the relationships between individual datasets in a novel and meaningful way.

Mining Interaction Patterns in the Design of Web Applications for Improving User Experience

The key success factor for modern web applications is their acceptance by the end-users which heavily depends on the quality of the user experience that they offer to them. Users require applications designed in such a way that it enables them to learn the supported functionalities easily, so that they can quickly find the information that they are looking for. Therefore, the usability and the overall design quality of an application can determine its success or failure. In this paper, we analyze the conceptual model of CMS-based web applications in terms of the incorporated design fragments that support the various user interaction processes. We consider these fragments as recurrent interaction patterns occurring in the application model, consisting of a configuration of front-end interface components that interrelate each other and interact with the user to achieve certain functionality. We have developed a methodology that automatically extracts the conceptual model of a web application and subsequently performs a pattern-based analysis of the model in order to identify the occurrences of all the recurrent interaction patterns. Finally, we calculate evaluation metrics revealing whether these patterns are used consistently throughout the application design. By utilizing these patterns, developers can produce more consistent and predictable designs, improving the ease of use of web applications.

Towards an era of epidemiological databases for autoimmune diseases

Nowadays, autoimmune diseases are among the leading causes of death for a remarkable number of patients all around the world. Recent studies have witnessed that the epidemiological indices for a specific disease can vary according to ethnic and geographical parameters. As a result, the genetic epidemiology of autoimmune diseases is a major matter of study for the worldwide scientific community. We have previously reported the development of dAUTObase (www.dAUTObase.org), a database recording solely epidemiological data of autoimmune diseases in various populations around the globe. Here, we present an important upgrade of the dAUTObase system focused on the development of new data visualization tools oriented to further assist the effective data querying and the mining process.

Mobile Data Fusion for Maritime Surveillance

Maritime surveillance operations are needed worldwide to monitor and reassure safety and security across the seas. Numerous devices are employed in order to provide situational awareness of the vast sea. Lots of different technologies are involved to provide multiple views and clarify maritime conditions at a given time and place, however making interoperability a real challenge. The task is even more tedious as there is a key request to provide a single window view for multiple even all possible inputs. In this work we present an integrated mobile fusion solution for multiple tracking and monitoring sensors (e.g. low weight/high performance radar, position transmission mechanisms and electro-optic/systems and hyper-spectral sensors) to assist the detection and early identification and tracking of moving targets (e.g. with moving target indication and data fusion/correlation capabilities), as well as methods for obstacle detection and maritime surveillance. This innovative single window mobile platform presents high efficiency, low operational costs profiles and contributes to standardization in construction as it utilizes typical tracking infrastructure and standard smartphones and tablets.

Mining Domain-Specific Design Patterns: A Case Study †

Domain-specific design patterns provide developers with proven solutions to common design problems that arise, particularly in a target application domain, facilitating them to produce quality designs in the domain contexts. However, research in this area is not mature and there are no techniques to support their detection. Towards this end, we propose a methodology which, when applied on a collection of websites in a specific domain, facilitates the automated identification of domain-specific design patterns. The methodology automatically extracts the conceptual models of the websites, which are subsequently analyzed in terms of all of the reusable design fragments used in them for supporting common domain functionalities. At the conceptual level, we consider these fragments as recurrent patterns consisting of a configuration of front-end interface components that interrelate each other and interact with end-users to support certain functionality. By performing a pattern-based analysis of the models, we locate the occurrences of all the recurrent patterns in the various website designs which are then evaluated towards their consistent use. The detected patterns can be used as building blocks in future designs, assisting developers to produce consistent and quality designs in the target domain. To support our case, we present a case study for the educational domain.