Overview

This knowledge graph synthesizes Arcadia Science's pioneering open research, spanning everything from how they reinvented scientific publishing to cutting-edge work in evolutionary biology and protein science.

Arcadia operates as an "open science" organization, publishing all research openly and sharing methods, data, and tools freely. This graph captures not just their scientific findings, but also their methodological innovations—like how they transitioned from a traditional publishing model to scientist-led, streamlined workflows.

The research spans diverse domains: petabase-scale viral discovery, tick protease inhibitors, cheese microbiome phage interactions, actin cytoskeleton evolution in green algae, and machine learning tools for biological clustering. This diversity is unified by a commitment to open methodology and evolutionary thinking.

What's in This Graph

• **7,157 knowledge nodes** across evolutionary biology, protein science, and methodology
• **200+ open publications** from Arcadia's research output
• **Publishing evolution** documenting the transition to scientist-led open science
• **Protein structure-function** relationships using TM-score and structural alignment
• **Viral discovery** methods using petabase-scale sequence alignment
• **46 identified research gaps** highlighting opportunities for future work

Questions You Can Explore

• How did Arcadia change its publishing model?
• What's the connection between protein structure and function?
• How are new viruses discovered from sequencing data?
• What protease inhibitor families exist in ticks?
• Which ML tools are used for biological clustering?
• What explains E. coli antibiotic resistance?

Data Access

Download: JSON Data

Citation: Fylo. (2025). Arcadia Science Research Knowledge Graph. https://fylo.io/arcadia

License: CC BY 4.0 - Free to use with attribution