Medical Systems Biology
JANet
JANet (Javascript AgeFactDB Network-viewer) is a specialized 3D Network Exploration and Visualization for Lifespan Data Exploration from AgeFactDB.
Features
- Interactive 3D network visualization (rotate, zoom, etc.)
- 2D representation
- Stereo representation (side by side)
- 3D beamer mode (condensed side by side stereo, converted for shutter glasses)
- Ageing-related network data (AgeFactDB)
- Lifespan observations
- Ageing factors
- Augmentation nodes (e.g.: allele types, citations)
- Augmentation with external domain knowledge
- Gene Ontology (GO)
- KEGG Pathways
- Genes of interest analysis (e.g.: differentially expressed genes)
- Scripting language
- JANet-specific API
Installation
The viewer can be started directly from the server at
https://sysbio.uni-ulm.de/software/janet
or the source code can be downloaded for local installation
(https://sysbio.uni-ulm.de/software/janet/latest.zip).
For a local installation there are two options:
- Extract the archive somewhere in the file system.
- Install a web server locally and extract the archive somewhere below the server root directory.
- Install a neo4j server
- python 3.5 or above is required.
Citing JANet
To cite the network viewer in publications, use:
Hühne H, Kessler V, Fürstberger A, Kühlwein S, Platzer M, Sühnel J, Lausser L, Kestler HA. 3D Network exploration and visualisation for lifespan data. BMC Bioinformatics 19(1): 390, 2018. https://doi.org/10.1186/s12859-018-2393-x
Latest News
Our first quantum computing paper "Leveraging quantum computing for dynamic analyses of logical networks in systems biology" has been published in Patterns.
Our paper "Unsupervised domain adaptation for the detection of cardiomegaly in cross-domain chest X-ray images" has been published in Frontiers in Artificial Intelligence.
- "The HLA ligandome of oropharyngeal squamous cell carcinomas reveals shared tumour-exclusive peptides for semi-personalised vaccination" has been published online first in the British Journal of Cancer.
"Vaccine Side Effects in Health Care Workers after Vaccination against SARS-CoV-2: Data from TüSeRe:exact Study" has been published in Viruses-Basel.
"PREDICT-juvenile-stroke: PRospective evaluation of a prediction score determining individual clinical outcome three months after ischemic stroke in young adults – a study protocol" has been published in BMC Neurology.
Our paper "Federated Electronic Data Capture (fEDC): Architecture and Prototype" has been accepted for publiaction in the Journal of Biomedical Informatics.
Our paper "Efficient cross-valdation traversals in feature subset selection" has been published in Scientific Reports.
Our paper "CANTATA - prediction of missing links in Boolean networks using genetic programming" has been published in Bioinformatics.
Our paper "Interaction Empowerment in Mobile Health: Concepts, Challenges, and Perspectives" has been published in the Journal of Medical Internet Research mhealth and uhealth.
Our paper "Identification of dynamic driver sets controlling phenotypical landscapes" has been published in the Computational and Structural Biotechnology Journal.
Congratulations to Dr. Silke Werle for winning the 1st Prize with her pitch at the 1. Science Day held by ProTrainU.
Our paper "Reconstructing Boolean network ensembles from single-cell data for unraveling dynamics in the aging of human hematopoietic stem cells" has been published in the Computational and Structural Biotechnology Journal.
The position paper "Is there a role for statistics in artificial intelligence" has been published online first in Advances in Data Analysis and Classification.