Longevity Atlas: Building a Decentralized Knowledge Network with Agentic Research Hypothesis Engine
Problem Statement:
The longevity research landscape is expanding exponentially, with thousands of papers published yearly across multiple hallmarks of aging. This information overload creates significant challenges for researchers trying to identify meaningful signals within the noise. This track challenges participants to develop a comprehensive decentralized knowledge graph system that spans all hallmarks of aging. A key component will be an autonomous research engine, built upon this graph, focused on generating novel scientific hypotheses.
Challenge:
Create a decentralized knowledge network that comprehensively maps all hallmarks of aging. Develop an autonomous hypothesis generation engine that leverages this network.
Comprehensive Knowledge Cartography: Construct an integrated knowledge graph spanning all 12 hallmarks of aging, highlighting not only established pathways within each hallmark but critically identifying interactions and emerging connections across the knowledge graph.
Autonomous Hypothesis Generation Engine: Develop an autonomous engine, utilizing the knowledge graph, that generates testable hypotheses. Each hypothesis must include the contextual evidence that underpins its plausibility (e.g., supporting embeddings retrieved from a vector database, or traversed nodes from the knowledge graph). This engine should draw on insights from cutting-edge research in the longevity field, such as the ongoing funded research by VitaDAO, to propose novel research directions.
Decentralized Knowledge Integration: Utilize OriginTrail's DKG plugin to write findings to a shared knowledge layer. Your BioAgents should automatically add new nodes and edges to the publicly accessible "BioGraph" as they process and analyze scientific literature.
Hallmarks of Aging to Include:
Genomic Instability - DNA damage accumulation and repair mechanisms
Telomere Attrition - Progressive shortening of chromosome ends
Epigenetic Alterations - Changes in gene expression without DNA sequence changes
Loss of Proteostasis - Impaired protein quality control systems
Deregulated Nutrient Sensing - Dysregulation of metabolic pathways
Mitochondrial Dysfunction - Decline in mitochondrial function and bioenergetics
Cellular Senescence - Accumulation of non-dividing cells
Stem Cell Exhaustion - Decline in regenerative potential
Altered Intercellular Communication - Dysregulation of signaling between cells
Chronic Inflammation - Persistent low-grade inflammation (inflammaging)
Dysbiosis - Alterations in microbiome composition and function
Extracellular Matrix Stiffening - Changes in tissue architecture and mechanics
Evaluation Metrics:
Scientific Accuracy: Correctness of extracted information and biological connections
Knowledge Organization: Quality and usefulness of knowledge graph structure
Cross-Hallmark Integration: Effectiveness of connecting mechanisms across different aging hallmarks
Automated Research Quality: Sophistication of hypothesis generation and peer review systems
Hypothesis Evidence: Quality and relevance of contextual evidence (e.g., embeddings, traversed nodes of knowledge graph) provided for each hypothesis
DKG Implementation: Effective use of DKG technology and contribution to the BioGraph
Implementation Quality: Code quality, documentation, and reproducibility
User Experience: Quality of visualizations, interface design, and system usability
Desired Outcomes:
Comprehensive knowledge graph encompassing all hallmarks of aging.
Contribution to the public "BioGraph" using fork of OriginTrail's DKG plugin
Interactive visualization system allowing exploration of the integrated longevity knowledge landscape and mapping of VitaDAO's research projects.
Automated research engine that generates novel, testable hypotheses based on the knowledge graph, including supporting contextual evidence (e.g., embeddings, traversed nodes of knowledge graph).
Documentation on system architecture, data sources, and knowledge graph ontology
Bank of Papers
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