3D Network exploration and visualisation for lifespan data

Area of Science:

• Gerontology and Bioinformatics
• Computational Biology and Data Visualization

Background:

• The Ageing Factor Database (AgeFactDB) houses extensive lifespan observations for ageing-related factors across various organisms.
• Quantitative data on genetic interventions and lifespan manipulations are available, necessitating advanced analysis beyond static queries.
• Complex relationships within ageing data benefit significantly from sophisticated exploration tools like 3D visualization.

Purpose of the Study:

• To develop and present novel network and visualization strategies for exploring complex ageing factor data.
• To introduce JANet, a Javascript 3D network viewer tailored for AgeFactDB, enabling interactive data analysis.
• To demonstrate how enhanced visualization aids in uncovering lifespan data patterns.

Main Methods:

• Development of diverse network visualization strategies, from single-species to multi-species networks.
• Integration of annotation nodes (e.g., Gene Ontology terms) to augment lifespan observation networks.
• Implementation of JANet, a custom Javascript 3D network viewer for interactive exploration of AgeFactDB data and gene lists.

Main Results:

• Proposed network types and visualization strategies facilitate the analysis of ageing factors.
• Augmented networks with annotation nodes accelerate data analysis.
• JANet enables interactive 3D visualization and analysis of lifespan data, including gene lists.

Conclusions:

• Interactive 3D network visualization complements traditional database queries for exploring complex lifespan data.
• The JANet interface provides deeper insights into lifespan data patterns than standard queries alone.
• The visualization concepts presented have broad applicability in other research domains.