ArticleScientific reports2015
Network fingerprint: a knowledge-based characterization of biomedical 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 8 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
8 citing papers in PubMed.
- Spectral divergence prioritizes key classes, genes, and pathways shared between substance use disorders and cardiovascular disease.Frontiers in neuroscience · 2025Article
- Human microRNA similarity in breast cancer.Bioscience reports · 2021Article
- MicroRNA Profiling in Aging Brain of PSEN1/PSEN2 Double Knockout Mice.Molecular neurobiology · 2018Article
- paraGSEA: a scalable approach for large-scale gene expression profiling.Nucleic acids research · 2017Article
- Investigating MicroRNA and transcription factor co-regulatory networks in colorectal cancer.BMC bioinformatics · 2017Article
- NFPscanner: a webtool for knowledge-based deciphering of biomedical networks.BMC bioinformatics · 2017Article
- NFP: An R Package for Characterizing and Comparing of Annotated Biological Networks.BioMed research international · 2017Article
- Neuroendocrine immunomodulation network dysfunction in SAMP8 mice and PrP-hAβPPswe/PS1ΔE9 mice: potential mechanism underlying cognitive impairment.Oncotarget · 2016Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
It can be difficult for biomedical researchers to understand complex molecular networks due to their unfamiliarity with the mathematical concepts employed. To represent molecular networks with clear meanings and familiar forms for biomedical researchers, we introduce a knowledge-based computational framework to decipher biomedical networks by making systematic comparisons to well-studied "basic networks". A biomedical network is characterized as a spectrum-like vector called "network fingerprint", which contains similarities to basic networks. This knowledge-based multidimensional characterization provides a more intuitive way to decipher molecular networks, especially for large-scale network comparisons and clustering analyses. As an example, we extracted network fingerprints of 44 disease networks in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. The comparisons among the network fingerprints of disease networks revealed informative disease-disease and disease-signaling pathway associations, illustrating that the network fingerprinting framework will lead to new approaches for better understanding of biomedical networks.
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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.