Towards An Era Of Epidemiological Databases For Autoimmune Diseases

Transcription

1 IEEE 12 TH INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOENGINEERING NOVEMBER 11-13, LARNACA, CYPRUS Towards An Era Of Epidemiological Databases For Autoimmune Diseases Vassiliki Gkantouna 1, Marina Ioannou 1, Athanassios Tsakalidis 1, Emmanouil Viennas 1 Konstantinos Poulas 2 John Tsaknakis 3, Giannis Tzimas 3 1 Department of Computer Engineering and Informatics, University of Patras, 2 Department of Pharmacy, University of Patras, 3 Department Of Applied Informatics in Management & Economy, TEI of Messolonghi

2 Overview Motivation dautobase: System Architecture, Conclusions Future Work

3 Motivation The genetic epidemiology of autoimmune diseases (ADs) is a major matter of study for the worldwide scientific community. Spatial epidemiology (geoepidemiology) dimension/perspective of ADs

4 Motivation dautobase is the first attempt to register a large number of epidemiological studies on ADs, to combine them with geographical and statistical parameters and to visualize the results in order to mine valuable information. We are currently experimenting on various visualization techniques in an effort to set the scene for a new interesting and promising area in the field of ADs, called geoepidemiological databases.

5 System Architecture dautobase is a web application recording solely epidemiological data of ADs in various populations around the globe. dautobase can be accessed at: It is based on a relational database developed with Microsoft SQL Server.

6 System Architecture Database records include: the population the geographic region the relative publication a number of epidemiological indices like incidence, prevalence, mortality, morbidity, age at onset etc.

7 System Architecture The system architecture is based on a three-tier model. It is made out of three main components: the client application, the application server and the database server. The n-tier architecture is a robust model and flexible enough to aggregate multiple information sources and integrate modular developments.

8 dautobase provides a web-based multimedia visualization environment for population-based ADs epidemiological data collection and retrieval. We have critically collected and screened a large number of epidemiological studies on ADs, analyzing their frequencies in various populations around the globe.

9 We have developed a data visualization framework for the dautobase data collection in order to provide a high level visualization of the data and the mining process. Three alternative querying interfaces: PivotViewer Disease Treemap Disease Worldmap

10 Sophisticated data exploration Users can apply advanced filtering criteria upon a set of multiple views of the same underlying data collection, giving them an active role in the mining process. This way, users can detect the links between distant data items and handle them in a way that intuitively reflects their semantic proximity.

11 dautobase PivotViewer application: is based on Microsoft Silverlight PivotViewer Control» The form of a card is used for the representation of each AD, in order to provide a more human-centric visualization approach.

12 The dautobase data collection, as produced by PivotViewer

13 dautobase PivotViewer application provide users the possibility to: interact with thousands of objects at once, and categorize and browse the screened data in multiple ways so that they can reveal new trends in them. zoom-in from the extensive dautobase datasets to particular disease-specific and/or population-specific data experiment with different querying scenarios, he/she may sometimes result in making incidental discoveries of potentially high medical importance (the discovery of demographic patterns, extraction of population-based patient characteristics).

14 PivotViewer query example

15 Disease Treemap: is based on the Flare Visualization Toolkit Treemaps are a space-filling approach of showing hierarchies in which the rectangular screen space is divided into regions, and then each region is divided again for each level in the hierarchy.

16 dautobase Disease Treemap presents the incidence rates of ADs over populations, with each rectangle representing the specific incidence rate of an AD within a specific population

17 The color of each rectangle corresponds to a different population The area of each rectangle encodes the incidence rate of the AD in the specified population. By clicking on a rectangle, users can query disease distrinbutions: dautobase Disease Treemap displays all the relative populations having less than 10% average difference of incidence.

18 Disease Treemap query example

19 Disease World Map: is based on the JQVMap It is a visual depiction of the worldwide map enriched with a variety of epidemiological indices per population

20 The color scale, corresponding to each country, depends on the screened data and reflects the value of the selected index for the specified disease and population. By hovering or clicking on a specific country, an additional information panel appears on the left, presenting: details like the name, the flag and the value of the selected index for the specified population (the selected country is always denoted by the green color).

21 Disease World Map query example Users can query disease distributions and correlations among populations. Query output screen for (A) the overall, (B) the women and (C) the men incidence rate of Type 1 Diabetes in different populations around the world.

22 Conclusions dautobase is the first attempt towards the establishment of geoepidemiological databases for ADs dautobase can serve as an alternative, effective and valuable online tool for web search in the context of autoimmune diseases and epidemiology Our primary goal is to offer a robust and stable tool oriented to support and broaden multidisciplinary knowledge among the scientists worldwide.

23 Future Work Experiment on more querying and alternative visualization types Implement an administration environment for dautobase Incorporate data mining techniques to further enhance and automate the discovery of valuable information Expose dautobase dataset through web services based on the odata protocol giving the ability to the research community to freely exploit our data.

24 QUESTIONS THANK YOU