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Updated: Nov 22, 2025

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics

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Published on: October 19, 2021

Interacting Discovery Processes on Complex Networks.

Iacopo Iacopini^1,2,3, Gabriele Di Bona^1,4, Enrico Ubaldi⁵

¹School of Mathematical Sciences, Queen Mary University of London, London E1 4NS, United Kingdom.

Physical Review Letters

|January 7, 2021

Summary

This summary is machine-generated.

Social networks accelerate innovation by connecting explorers. Centrality within these networks significantly impacts an individual

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Area of Science:

Complex systems science
Sociology of innovation
Network theory

Background:

Innovation drives human progress, with existing models capturing novelty-driven discovery.
Previous models overlooked the crucial impact of social interactions on the innovation process.
Understanding collective exploration is key to advancing discovery dynamics.

Purpose of the Study:

To model collective exploration mechanisms within a social network structure.
To investigate how social connections influence the pace and spread of discovery.
To analyze the role of network centrality in individual and collective innovation.

Main Methods:

Developed a multi-urn model where explorers (urns) are interconnected via a social network.
Simulated the exploitation of opportunities through social contacts.
Employed analytical and numerical methods to study various network structures.

Main Results:

Explorer's discovery pace is directly correlated with their centrality in the social network.
Network structure significantly modulates the dynamics of collective discovery.
Social interactions amplify the cascading effect of novel discoveries.

Conclusions:

Social structures are fundamental determinants of discovery processes in innovation.
Network centrality emerges as a critical factor for individual and collective exploration success.
The proposed model provides insights into the interplay between social dynamics and innovation.