ArticleBMC research notes2017
NAP: The Network Analysis Profiler, a web tool for easier topological analysis and comparison of medium-scale biological networks.
Article in BMC research notes, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
16 citing papers in PubMed.
- In-silico identification of therapeutic targets in pancreatic ductal adenocarcinoma using WGCNA and Trader.Scientific reports · 2024Article
- Bioinformatics Prediction for Network-Based Integrative Multi-Omics Expression Data Analysis in Hirschsprung Disease.Biomolecules · 2024Article
- Time-resolved proteomic profiling reveals compositional and functional transitions across the stress granule life cycle.Nature communications · 2023Article
- Single-cell sequencing and transcriptome analyses in the construction of a liquid-liquid phase separation-associated gene model for rheumatoid arthritis.Frontiers in genetics · 2023Article
- NORMA: The Network Makeup Artist - A Web Tool for Network Annotation Visualization.Genomics, proteomics & bioinformatics · 2022Article
- Darling: A Web Application for Detecting Disease-Related Biomedical Entity Associations with Literature Mining.Biomolecules · 2022Article
- A Bioinformatics-Assisted Review on Iron Metabolism and Immune System to Identify Potential Biomarkers of Exercise Stress-Induced Immunosuppression.Biomedicines · 2022Review
- Biomolecule and Bioentity Interaction Databases in Systems Biology: A Comprehensive Review.Biomolecules · 2021Review
- Biological Network Mining.Methods in molecular biology (Clifton, N.J.) · 2021Article
- NetConfer: a web application for comparative analysis of multiple biological networks.BMC biology · 2020Article
- A Guide to Conquer the Biological Network Era Using Graph Theory.Frontiers in bioengineering and biotechnology · 2020Review
- WIPER: Weighted in-Path Edge Ranking for biomolecular association networks.Quantitative biology (Beijing, China) · 2019Article
- Age-based dynamic changes of phylogenetic composition and interaction networks of health pig gut microbiome feeding in a uniformed condition.BMC veterinary research · 2019Article
- CatbNet: A Multi Network Analyzer for Comparing and Analyzing the Topology of Biological Networks.Current genomics · 2019Article
- HipMCL: a high-performance parallel implementation of the Markov clustering algorithm for large-scale networks.Nucleic acids research · 2018Article
- Bipartite graphs in systems biology and medicine: a survey of methods and applications.GigaScience · 2018Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveNowadays, due to the technological advances of high-throughput techniques, Systems Biology has seen a tremendous growth of data generation. With network analysis, looking at biological systems at a higher level in order to better understand a system, its topology and the relationships between its components is of a great importance. Gene expression, signal transduction, protein/chemical interactions, biomedical literature co-occurrences, are few of the examples captured in biological network representations where nodes represent certain bioentities and edges represent the connections between them. Today, many tools for network visualization and analysis are available. Nevertheless, most of them are standalone applications that often (i) burden users with computing and calculation time depending on the network's size and (ii) focus on handling, editing and exploring a network interactively. While such functionality is of great importance, limited efforts have been made towards the comparison of the topological analysis of multiple networks.
resultsNetwork Analysis Provider (NAP) is a comprehensive web tool to automate network profiling and intra/inter-network topology comparison. It is designed to bridge the gap between network analysis, statistics, graph theory and partially visualization in a user-friendly way. It is freely available and aims to become a very appealing tool for the broader community. It hosts a great plethora of topological analysis methods such as node and edge rankings. Few of its powerful characteristics are: its ability to enable easy profile comparisons across multiple networks, find their intersection and provide users with simplified, high quality plots of any of the offered topological characteristics against any other within the same network. It is written in R and Shiny, it is based on the igraph library and it is able to handle medium-scale weighted/unweighted, directed/undirected and bipartite graphs. NAP is available at http://bioinformatics.med.uoc.gr/NAP .
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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.