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20042026
most citedStructure and dynamics of molecular networks: A novel paradigm of drug discovery. A comprehensive review

916 citations

Showing q-bio.MNShow all

31 papers · 1 filter

q-bio.MN2023★ 14 cited

Cellular forgetting, desensitisation, stress and aging in signalling networks. When do cells refuse to learn more?

Tamas Veres, Mark Kerestely, Borbala M. Kovacs +6

Recent findings show that single, non-neuronal cells are also able to learn signalling responses developing cellular memory. In cellular learning nodes of signalling networks stren…

q-bio.MN2021★ 30 cited

Synaptic polarity and sign-balance prediction using gene expression data in the Caenorhabditis elegans chemical synapse neuronal connectome network

Bank G. Fenyves, Gabor S. Szilagyi, Zsolt Vassy +2

Graph theoretical analyses of nervous systems usually omit the aspect of connection polarity, due to data insufficiency. The chemical synapse network of Caenorhabditis elegans is a…

q-bio.MN2020★ 71 cited

Learning of signaling networks: molecular mechanisms

Péter Csermely, Nina Kunsic, Péter Mendik +4

Molecular processes of neuronal learning have been well-described. However, learning mechanisms of non-neuronal cells have not been fully understood at the molecular level. Here, w…

q-bio.MN2019★ 35 cited

The EntOptLayout Cytoscape plug-in for the efficient visualization of major protein complexes in protein-protein interaction and signalling networks

Bence Agg, Andrea Csaszar, Mate Szalay-Beko +5

Motivation: Network visualizations of complex biological datasets usually result in 'hairball' images, which do not discriminate network modules. Results: We present the EntOptLayo…

q-bio.MN2018★ 19 cited

Translocatome: a novel resource for the analysis of protein translocation between cellular organelles

Peter Mendik, Levente Dobronyi, Ferenc Hari +5

Here we present Translocatome, the first dedicated database of human translocating proteins. The core of the Translocatome database is the manually curated data set of 213 human tr…

q-bio.MN2015★ 20 cited

The wisdom of networks: A general adaptation and learning mechanism of complex systems: The network core triggers fast responses to known stimuli; innovations require the slow network periphery and are encoded by core-remodeling

Peter Csermely

I hypothesize that re-occurring prior experience of complex systems mobilizes a fast response, whose attractor is encoded by their strongly connected network core. In contrast, res…