ReviewBiophysical reviews2025
Structural determinants of soft memory in recurrent biological networks.
Review in Biophysical reviews, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
- Biophysical reviews (ISSUE 2 2025): LAFeBS, alive, kicking, and growing: the story continues...Biophysical reviews · 2025Article
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Recurrent neural networks are frequently studied in terms of their information-processing capabilities. The structural properties of these networks are seldom considered, beyond those emerging from the connectivity tuning necessary for network training. However, real biological networks have non-contingent architectures that have been shaped by evolution over eons, constrained partly by information-processing criteria, but more generally by fitness maximization requirements. Here, we examine the topological properties of existing biological networks, focusing in particular on gene regulatory networks in bacteria. We identify structural features, both local and global, that dictate the ability of recurrent networks to store information on the fly and process complex time-dependent inputs.
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Registered trials
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