- Walking Wales: the visualisation challenge
- Word Clouds: Can they be misleading?
- VIPS-Visual Interactive Parameter Steering
- Confirmation bias : do multiple views really help?
- Visual Query Interface for Infrastructure Networks
- MADucator – Matrix Educator
- Concensus Matrix Sort
- Multiscale Multiples: An Overview+Detail Interface for Small Multiples
- Analyzing Image Similarity to Detect Disguised Plagiarism
- Tackling the Multi-Analyst Problem in Soccer: How to Improve Collaborative Pattern Detection in Team Sports
- MDSQ – Quality Assessment of Distance-Preserving Projections
- Internal Quality Measures for Subspace Clusterings
- Exploration of Datasets for Visualizations of High-Dimensional Data
- Search and Visual Exploration of Scientific Literature
- Star Glyph – Optimal Dimension Layout
- Visual Analytics of Molecular Neurochemicals and Biological Markers in Mental Illness
- Ensembles of classifiers: Visual construction of classification models
- Cutting-Down the Complexity of Parallel Coordinates Plots in High-Dimensional Data
- Investigating Analytic Behavior in VA
- Hierarchical Matrix Visualization
- Realisierung und Evaluierung einer stereoskopischen 3D Perspective Wall Umgebung für verlinkte Informationsvisualisierung (Master)
- Combination of Matrices + Graphs
- TreeMap Evaluation
- Visual Analysis of Language Change over Time
- Visual Parameter Space Analysis of Topic Models
The main goal of this project is to develop a visual analytics tool for molecular psychiatry research and analysis to get insight into the relationship between biological markers and different mental illness.
Overview and Background
Schizophrenia and affective disorders such as mania and depression are usually labeled under the umbrella of the generic term “psychosis”. Nevertheless, the aethiology of schizophrenia itself is not fully understood.
In order to find a rational explanation for schizophrenia a variety of hypotheses have been attempted over the years. A well-known theory is the so-called trans-methylation theory of schizophrenia, which seems to fit the observed facts related to indolealkylamines.
The interdisciplinary work of scientists from biological psiquiatry, neurosciences, and computer science can lead to a better understanding of the causation of mental illness, such as schizophrenia, and therefore a correct diagnosis and effective treatment.
Visual Analytics can be very helpful for the hypothesis generation process, inspection of neurochemicals and biological markers, and verification of the diagnosis.
The exploration of molecular data by means of machine learning techniques and visual analytics can provide a novel approach for the analysis of the biological mechanisms underlying psichiatric disorders and their treatment.
- Literature review for visual analytics, comparative multivariate visualization.
- Development of a visual-interactive tool for the visual inspection of biological traces in psiquiatric patients.
- Knowledge in information visualization.
- Scope: Bachelor/Master
- 6 Month Project, 3 Month Thesis (Bachelor) / 6 Month Thesis (Master)
- Start: immediately
|Theoretical (Analytical):||(5 / 5)|
|Practical (Implementation):||(5 / 5)|
|Literature Work:||(4 / 5)|
- Clinical implications of small molecule-methyltransferases [Ciprian et al., 2016]
- Cult-Hoasca: A Model for Schizophrenia [Pomilio et al., 2003]
- Scientists’ sense making when hypothesizing about disease mechanisms from expression data and their needs for visualization support [Mirel and Görget, 2014]