Introduction
JANet Description
JANet (Javascript AgeFactDB Network-viewer) is a specialized 3D network viewer for the visualization of ageing-related network data from AgeFactDB.

Selected Features
- Interactive 3D network visualization(rotate, zoom, etc.)
- 2D representation
- Stereo representation(e.g.: side by side)
- 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
Requirements
- 4 GB main memory
- Modern Web browser with activated Javascript
Recommended:
- 16 GB main memory
- 64-bit system
- Modern web browser with activated Javascript
Availability
JANet is available at the web address http://sysbio.uni-ulm.de/?Software:JANet.
Installation
No installation needed! JANet runs directly in your web browser.
The viewer can be started from server at http://sysbio.uni-ulm.de/software/janet
AgeFactDB
Description
AgeFactDB (http://agefactdb.jenage.de) is a database aimed at the collection and integration of ageing phenotype data including lifespan information.
Ageing factors are considered to be genes, chemical compounds or other factors such as dietary restriction, whose action results in a changed lifespan or another ageing phenotype.
Any information related to the effects of ageing factors is called an observation and is presented on observation pages. To provide concise access to the complete information for a particular ageing factor, corresponding observations are also summarized on ageing factor pages.
In a first step, ageing-related data were primarily taken from existing databases such as the Ageing Gene Database--GenAge, the Lifespan Observations Database and the Dietary Restriction Gene Database--GenDR. In addition, it was started to include new ageing-related information.
Based on homology data taken from the HomoloGene Database, AgeFactDB also provides observation and ageing factor pages of genes that are homologous to known ageing-related genes. These homologues are considered as candidate or putative ageing-related genes.
Ageing Factors
Currently there are implemented three types of ageing factors: Gene, Chemical Compound, and Other Ageing Factor.
Gene
If available, the NCBI Gene ID is used for the identification of genes, to avoid duplicate entries with different names.
If it is not provided, it is tried to assign it automatically using the synonym database GPSDB and the NCBI Gene database. If multiple NCBI Gene IDs might match, no NCBI Gene ID is assigned and only gene symbol and species are used for the integration
Internally always gene symbol, species, and NCBI Gene ID are used to identify a gene. Depending on the information provided by the data source, GPSDB, and NCBI Gene it is possible that the same gene symbol/species combination is included multiple times into AgeFactDB, with and without one or more different NCBI Gene IDs.
Chemical Compound
Chemical compounds are currently identified by the name who was used in the AgeFactDB source databases. No synonym information is used yet within AgeFactDB.
Other Factor
Other factors are for example dietary restriction and heat shock.
Similar to chemical compounds they are currently only identified by their name. Because it is difficult to judge the slight differences that might be involved for example between 'dietary restriction' and 'caloric restriction', it wasn't done any unification yet.
Putative Ageing Factors
In addition to genes with experimental ageing relevance evidence, AgeFactDB includes also genes homologous to these genes as putative ageing factors. They are identified by a homology analysis based on the HomoloGene database from the NCBI.
In contrast to other ageing-related databases, where homologous genes are just named inside a gene page, they are included in the same way as the genes with experimental ageing relevance evidence. This way the full features are also available for the putative ageing factors.
Ageing factors are discriminated from putative ageing factors inside the AgeFactDB web interface by a color coding system shown in the Figure below. Green indicates experimental evidence with an effect on ageing, red indicates experimental evidence with no effect on ageing, and blue indicates computational ageing relevance evidence. The color of all observations assigned to an ageing factor determine the color of the ageing factor, with the following priority: green, red, blue. In addition to the major color, all other assigned colors are also indicated as small squares.

The priority for assigning a color to the ageing factor is indicated by the number:
- Highest priority – 1
- Lowest priority – 3
Observations
Currently there are implemented three types of observations:
- Ageing Phenotype Data Type 1
- Ageing Phenotype Data Type 2
- Homology Analysis
The names are the 'official' names used in the web interface. Initially, the first two types were named 'phenotype' and 'lifespan'. But this didn't really fit, because lifespan is also a phenotype and because some phenotype observations also contained lifespan data. So it was switched to a technical distinction:
- Data Type 1 - free-text ageing phenotype observations
- Data Type 2 - structured ageing phenotype observations
- Homology analysis - structured computational observations.
Unification
The same genes might have been integrated into two different source databases or even the same source database with different names.
It was tried to resolve this by using the gene/protein synonym database GPSDB and integrate the gene into AgeFactDB using the name marked as preferred name in GPSDB.
All name changes are listed in a table within the release page. A partial list of the ageing factor name changes as a result of the unification is shown below:

Network Data
The lifespan observation data from AgeFactDB was transformed into a network data representation.
Lifespan Observation/Ageing Factor Nodes
Each lifespan observation (LO) and each ageing factor (AF) is represented by a network node. Ageing factors involved in a specific lifespan observation are each linked to it by an edge. This facilitates to understand the often very complex system of observations involving overlapping sets of ageing factors at different conditions.
Annotation Nodes
Cruical annotation data is not just attached to an observation or ageing factor, visible for example while hovering a node. Instead it expands the network as annotation node (ANN).
AgeFactDB Annotation Nodes
JANet currently supports the following types of annotation nodes from AgeFactDB data:
- Allele Type (ALT)
- Citation (CIT)
- Species (SP)
Expert Knowledge Annotation Nodes
In addition to AgeFactDB-based annotation nodes, JANet also supports annotation nodes based on expert knowledge from other databases:
- Gene Ontology(GO)
- KEGG Metabolic Pathways (extracted from the BioSystems database)
Network Layout Algorithms
3D network visualization requires to define a position in the three-dimensional space for each node, called a network layout. Spring-force algorithms provide often useful layouts. In these algorithms connected nodes attract each other and unconnected nodes repel each other. The attracting and repelling forces are calculated like for spring forces in physics. As a start, the nodes are usually placed on random positions. The forces are then calculated for each node pair in an iterative process to define new node positions, until an equilibrium is reached or a fixed number of iterations.
Fruchterman-Reingold
JANet uses the Fruchterman-Reingold algorithm in an adapted version for 3D layout, implemented in Javascript. It generates good layouts for small to medium sized networks, up to a few hundred nodes.
FMMM - Fast Multipole Multilevel Method
For larger networks the FMMM (Fast Multipole Multilevel Method) algorithm used in BioLayout Express 3D, another 3D network viewer, provides better layouts than the Fruchterman-Reingold algorithm. It is not implemented in JANet yet, but JANet provides export/import options that enable to use BioLayout Express 3D as an external layout generation tool for larger networks.
Visualization Techniques
JANet provides several visualization techniques for lifespan observation (LO) networks of ageing factors (AFs).
Node color and size are used there to speed-up the lookup of node properties by visual perception for all nodes at once. Generally these properties are the node type and the qualitative and quantitative lifespan change.
The edge color is usually inherited from the node of a pair whose color carries specific information for the other node. For AF/LO edges this is the LO node, whose color usually indicates the direction of the lifespan change (increased, decreasd, none).
Direct Neighbourhood
The direct neighbourhood network provides a compact view of the effects of all LOs in which an AF is involved directly.

Color scheme: AF, LO - increased lifespan, LO - decreased lifespan
Complete Neighbourhood
The complete neighbourhood network provides an overview on all experimentally analyzed AF combinations and their effects on lifespan, originating from the AF in the focus.

Color scheme: AF, LO - increased lifespan, LO - decreased lifespan
Augmentation via Annotation Nodes
The augmented network provides additional information on either the AFs or the LOs or both by the integration as additional annotation nodes. This provides a quicker access to the additional information and leads to a semantic clustering of the AFs and LOs.

Color scheme: AF, LO - increased lifespan, LO - decreased lifespan, annotation
Data Transfer betwen Nodes
The data transfer between nodes is especially useful for reducing the complexity of a network by removing the nodes from which data was transferred. The transfer enables to retain some information from the removed nodes.

Color scheme: annotation, AF - linked only to LOs with increased lifespan,, AF - linked to LOs with highly mixed lifespan changes (increased and decreased > 20%)
Multispecies Technique
In contrast to genes, chemical compounds and other AFs can be linked to LOs of multiple species. This requires to augment such networks by species nodes (SP) that are linked to the corresponding LOs. The links between the AFs and the species nodes were left out. This will result in a much clearer and less complex network view, grouping the network clearly according to the involved organisms.
Because of the importance of the species information in these networks and the additional restriction to one type of species links a separate technique was defined.

- AF1 to SP1 via LO1, to SP2 via LO2, and to SP3 via LO3 and LO4
- AF2 to SP1 via LO1
- AF3 to SP3 via LO4
Color scheme: AF, LO - increased lifespan, LO - decreased lifespan, species
JANet Web Browser Interface
Overview
JANet has a modern web browser interface with eight tabs:
- Ageing Factor Networks
- Overview Networks
- Import Gene List
- Gene List Networks
- Viewer
- Info
- Contact / Imprint
- Help
Basics
Ageing Factor Networks
This tab can be used to choose a specific ageing factor along with it's annotation nodes. You can filter for species and then select an ageing factor. By default the direct neighbourhood of the ageing factor is selected, the complete neighbourhood can be used as well. By visualizing the network (Button Visualize) the Viewer is activated and the network is shown.
Overview Networks
To get an overview of a set of ageing factors, the second tab can be used to visualize these. A filter for species and a selection of annotation nodes can be choosen.
Import Gene List
If you want to analyse a secific gene set, you can upload your gene list to JANet and use the third tab to import your data and start the analysis. Genes matching with ageing factors from AgeFactDB are presented in tabular form. You can then select genes of interest for visualizing the corresponding lifespan observation network or get an overview network from the found genes of interest.
Viewer
Info
Some statistics for AgeFactDB and JANet are shown here.
Contact / Imprint
How to contact us.
Help
This help.