ArticleScientific reports2015
DeFiNe: an optimisation-based method for robust disentangling of filamentous networks.
Article in Scientific reports, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 17 citations in OpenAlex.
- GraFT: A robust network-based spatiotemporal analysis of filamentous structures.Science advances · 2026Article
- From Pixels to Patterns: A Multidimensional Framework to Decode Cytoskeletal Organization.Computational and structural biotechnology journal · 2026Review
- KnotResolver: tracking self-intersecting filaments in microscopy using directed graphs.Bioinformatics (Oxford, England) · 2024Article
- Automatic extraction of actin networks in plants.PLoS computational biology · 2023Article
- Tracing and tracking filamentous structures across scales: A systematic review.Computational and structural biotechnology journal · 2023Review
- Principled network extraction from images.Royal Society open science · 2021Article
- Automated and semi-automated enhancement, segmentation and tracing of cytoskeletal networks in microscopic images: A review.Computational and structural biotechnology journal · 2021Review
- Automated Tracking of Biopolymer Growth and Network Deformation with TSOAX.Scientific reports · 2019Article
- HyphaTracker: An ImageJ toolbox for time-resolved analysis of spore germination in filamentous fungi.Scientific reports · 2018Article
- System-wide organization of actin cytoskeleton determines organelle transport in hypocotyl plant cells.Proceedings of the National Academy of Sciences of the United States of America · 2017Article
- An integrated enhancement and reconstruction strategy for the quantitative extraction of actin stress fibers from fluorescence micrographs.BMC bioinformatics · 2017Article
- Extracting microtubule networks from superresolution single-molecule localization microscopy data.Molecular biology of the cell · 2017Article
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Thread-like structures are pervasive across scales, from polymeric proteins to root systems to galaxy filaments, and their characteristics can be readily investigated in the network formalism. Yet, network links usually represent only parts of filaments, which, when neglected, may lead to erroneous conclusions from network-based analyses. The existing alternatives to detect filaments in network representations require tuning of parameters over a large range of values and treat all filaments equally, thus, precluding automated analysis of diverse filamentous systems. Here, we propose a fully automated and robust optimisation-based approach to detect filaments of consistent intensities and angles in a given network. We test and demonstrate the accuracy of our solution with contrived, biological, and cosmic filamentous structures. In particular, we show that the proposed approach provides powerful automated means to study properties of individual actin filaments in their network context. Our solution is made publicly available as an open-source tool, "DeFiNe", facilitating decomposition of any given network into individual filaments.
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