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- Info
Sponsors
| Title |
Diagnostik der Tumorheterogenität – ein neuer Steuerfaktor für die Therapie des
Dickdarmkarzinoms? |
| Time period |
2012 - 2014 |
| Sponsor |
Das Land Steiermark
|
| Partner |
Medical University of Graz, IFZ – Interuniversitäres Forschungszentrum für
Technik, Arbeit und Kultur |
| Project Number |
GZ:A3-22.M-5/2012-21 |
| Abstract |
Das Kolonkarzinom ist weltweit eine der häufigsten Krebserkrankungen, die trotz
Fortschritte in der Behandlung nach Ausbildung von Metastasen fast immer zum Tod führt.
Gemäß internationalen Standards ist derzeit die pathohistologische Untersuchung
entscheidend für das therapeutische Vorgehen. Für Patienten in fortgeschrittenen
Tumorstadien wurden kürzlich Therapien verfügbar, die auf den Mutationsstatus des
Tumors ausgerichtet sind, jedoch eine mögliche Tumorheterogenität nicht
berücksichtigen. Derzeit nicht detektierte Tumorklone werden für das oft fehlende
Therapieansprechen und die Tumorprogression verantwortlich gemacht. Das beantragte
Projekt soll durch Anwendung neuer sensorischer Verfahren zur kosteneffizienten und
verlässlichen Bestimmung der genetischen Diversität von Dickdarmkarzinomen beitragen.
Mittels statistischer Verfahren und bioinformatischer Analyse der genetischen Profile
werden die Häufigkeit sowie die prognostische Bedeutung der Tumorheterogenität für das
biologische Verhalten der Tumore sowie ihr Ansprechen auf spezifische onkologische
Therapien ermittelt. Durch spezielle, an der TUG entwickelte Visualisierungstechniken
wird die erhobene Datenfülle für Pathologen und klinische Onkologen verständlich und
verwertbar gemacht. Eine umfassende genetische Tumoranalyse setzt das vollinhaltliche
Einverständnis des Patienten voraus, welches untrennbar mit dem Verständnis und der
Zustimmung zu den hierzu verwendeten Methoden verbunden ist. Ein weiteres Projektziel
ist daher die Untersuchung von Erwartungen und Hoffnungen aber auch von Vorbehalten
bzw. Befürchtungen, die in die Beratung und Aufklärung des Patienten Eingang finden
sollen und die die unterschiedlichen Einstellungen der Patienten zu den diagnostischen
Verfahren berücksichtigen. Diese neuen Diagnoseverfahren werden ein Ansprechen auf eine
Therapie wesentlich gezielter voraussagen können als die derzeitigen Methoden, den
Patienten Nebenwirkungen unwirksamer Medikamente ersparen und damit nicht zuletzt zu
einer Kostenreduktion im Gesundheitssystem beitragen. |
| Title |
Collaborative information visualization |
| Time period |
2011 - 2014 |
| Sponsor |
FWF Stand-alone Project
|
| Project Number |
P22902 |
| Abstract |
Critical decisions involving a lot of data are rarely made by a single person,
but are rather discussed and evaluated by a team of experts. Examples are doctors
deciding for treatment of severe illness, emergency services having to react to ongoing
crises, or engineers collaborating to make technical decisions concerning expensive
products. These activities can be assisted by information visualization tools. However,
traditional information visualization rarely considers the collaborative nature of data
analysis tasks. The foundation of our research proposal is the extension of a multiple
view visualization system to a multi-display environment. Multiple view visualization
shows data in different representations and thereby accommodates for different
knowledge backgrounds and user preferences. Multi-display environments turn unused wall
and table spaces into interactive surfaces using off-the-shelf projection technology
and integrate private workstations smoothly into this shared interactive workspace. Our
research aim is the design and creation of a co-located collaborative information
visualization workspace dealing with two principal challenges: display space management
and collaborative interaction techniques. Intelligent display space management adopts
information visualizations and placement of views automatically to the physical display
properties and supports the users interacting with the environment. Combined with
visual linking of related data entities distributed across the environment, it will
help to establish a common knowledge ground. Collaborative interaction techniques are
required to organize such a rich, but potentially complex environment. We will
investigate high-level activity support for typical tasks in shared information
workspaces and how users can maintain awareness of each other’s activities. The
proposed research benefits from two ongoing projects at Graz University of Technology:
Deskotheque delivers the basic technology necessary for collaborative work in
multi-display environments, while Caleydo, a visualization project from the biomedical
domain, provides an excellent use case, including the necessary experts willing to
collaborate in studies. Using these frameworks, we plan to conduct several usability
studies, with prototypes of different levels of sophistication. This research is
part of the project Caleydo.
|
| Title |
Holistic Visualization of Biomolecular and Clinical Data |
| Time period |
10.2009 - 12.2011 |
| Partner |
SimVis
|
| Sponsor |
FFG BRIDGE Program
|
| Grant Number |
385567 |
| Abstract (in German) |
Ziel des Projekts inGeneious ist es, Visualisierungsmethoden und Work-Flows zu
entwickeln, die Biologen und Medizinern bei der Analyse biomolekulare Daten im Kontext
von klinischen Faktoren sowie biologischen Prozesse unterstützen. Die Berücksichtigung
dieser Faktoren bei der Analyse von zum Beispiel Genexpressionsdaten ist entscheidend,
da auf diese Weise Rückschlüsse über Zusammenhänge von genetischer Predisposition und
Krankheitsverlauf gewonnen werden können. Zwei zentrale Forschungsfragen sind
Gegenstand des inGeneious-Projektes. Zunächst soll eine ganzheitliche Betrachtungsweise
der drei Datenräume durch Multiple-View-Verfahren und effizientes visuelles Verbinden
von Informationen ermöglicht werden. Darauf aufbauend soll eine vergleichende Analyse
divergierender Gruppen durch neue, vergleichende Visualisierungsmethoden ermöglicht
werden. Experten erhalten damit ein Werkzeug um die immer größer werdende Menge
biomolekularer Daten effizient verwenden zu können. |
| Title |
Visual Analytics for Personalized Medicine |
| Time period |
11.2007 - 04.2010 |
| Sponsor |
|
| Grant Number |
L427-N15 |
| Abstract |
VIPEM is an interactive data exploration system for the “visualization of” and
“navigation in” molecular and clinical data in the field of personalized medicine. A
multidimensional space consisting of molecular and clinical data is screened and
hierarchically structured by applying algorithmic methods and direct user interaction.
The essential but to date unsolved problem VIPEM addresses in the emerging field of
personalized medicine is the question of how to identify connections between genetic
variants and their corresponding diseases or the response to certain drugs and
treatments, respectively. It is therefore necessary, to e.g. connect gene data and
clinical data in order to categorise specific subgroups of patients with certain
diseases. The huge amount of data provided by molecular analytical methods (genetic
polymorphisms, gene expression data, proteomics) can only be accomplished by applying
bioinformatical and statistical methods. However, even standard methods of statistics
and bioinformatics fail when the data are inhomogeneous – as is the case with clinical
data – and when data structures are obscured by noise and dominant patterns.
VIPEM should make the structure of the data spaces visible by using visualisation
methods and allow an interactive navigation and structuring of both molecular and
clinical data. VIPEM is based on fundamental results in the fields of information
visualisation and multimodal user interfaces. Through a close link between several
input channels, which are simultaneously active, and by immediate visualisation of the
steps of the analysis, the expert is provided with a tool for the interactive
exploration of complex data spaces. As input parameter for analysis algorithms VIPEM
makes use of the human capacity to grasp complex patterns and correlations and
therefore allows to reveal hidden structures. VIPEM aims to address the high
demand for visual analytics in the field of bioinformatics. The innovative approach of
VIPEM can be a unique selling proposition in this market, in such a way that we can see
a promising commercial prospect for VIPEM and a marketable product within the period of
two to three years. The VIPEM team aims at exploiting results either through a spin-off
company or as strategic partner of an existing biomedical company. technology supplier
of an existing biomedical company. This research is part of the project Caleydo.
|
| Title |
Visual Data Mining for Genetic Data |
| Time period |
08.2007 - 07.2009 |
| Sponsor |
FFG FIT-IT Program 
|
| Grant Number |
813398 |
| Abstract |
Genoptikum is an interactive data exploration system for the visualization of
and navigation in molecular and clinical data in the field of personalized medicine.
Genoptikum addresses the essential but to date unsolved problem of how to identify
connections between genetic variants and their corresponding diseases or the response
to certain drugs and treatments, respectively. It is, therefore, necessary to connect
gene data and clinical data in order to categorise specific subgroups of patients with
certain disease features. The huge amount of data provided by molecular analytical
methods (genetic polymorphisms, gene expression data, proteomics) can only be analysed
by applying statistical methods and bioinformatics. However, even standard methods of
statistics and bioinformatics fail when the data are inhomogeneous as is the case with
clinical data and when data structures are obscured by noise and dominant patterns.
Genoptikum should make the structure of the data spaces visible by using innovative
methods of visualisation based on multiple high resolution displays in combination with
data projection technologies. Genoptikum is bases on fundamental results in the fields
of visualisation of information and multimodal user interfaces which enable an
interactive navigation and structuring of both molecular and clinical data. Through a
close link between several input channels, which are simultaneously active, and by
immediate visualisation of the steps of the analysis, the expert is provides with a
tool for the interactive exploration of complex data spaces. As input parameter for
analysis algorithms Genoptikum makes use of the human visual capacity to grasp complex
patterns to reveal hidden structures and correlations in large data spaces. This
research is part of the project Caleydo.
|
| Title (in German) |
Analyse von genetischen und klinischen Daten mit Methoden der
Informationsvisualisierung und multimodaler Benutzerschnittstellen |
| Time period |
2005 - 2007 |
| Sponsor |
Zunkunftsfond Steiermark |
| Abstract |
This project is concerned with the visualization of Microarray data using
multiple displays and visual data mining techniques. It was the first research activity
that led to the project Caleydo. |
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