ArticleSource code for biology and medicine2017
NET: a new framework for the vectorization and examination of network data.
Article in Source code for biology and medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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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Who cites it
6 citing papers in PubMed.
- Full identification of a growing and branching network's spatio-temporal structures.Biophysical journal · 2025Article
- From pixels to connections: exploring in vitro neuron reconstruction software for network graph generation.Communications biology · 2024Review
- An image based application in Matlab for automated modelling and morphological analysis of insect wings.Scientific reports · 2022Article
- Principled network extraction from images.Royal Society open science · 2021Article
- LeafScope: A Portable High-Resolution Multispectral Imager for In Vivo Imaging Soybean Leaf.Sensors (Basel, Switzerland) · 2020Article
- Computational analysis of size, shape and structure of insect wings.Biology open · 2019Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe analysis of complex networks both in general and in particular as pertaining to real biological systems has been the focus of intense scientific attention in the past and present. In this paper we introduce two tools that provide fast and efficient means for the processing and quantification of biological networks like
resultsNET is especially designed for high-throughput semi-automated analysis of biological datasets containing digital images of networks. The framework starts with the segmentation of the image and then proceeds to vectorization using methodologies from optical character recognition. After a series of steps to clean and improve the quality of the extracted data the framework produces a graph in which the network is represented only by its nodes and neighborhood-relations. The final output contains information about the adjacency matrix of the graph, the width of the edges and the positions of the nodes in space.
conclusionThe networks extracted by
Indexed as
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.