ArticleBMC research notes2011
Medusa: A tool for exploring and clustering biological networks.
Article in BMC research notes, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 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
23 citing papers in PubMed.
- A network biology approach to identify crucial host targets for COVID-19.Methods (San Diego, Calif.) · 2022Article
- NORMA: The Network Makeup Artist - A Web Tool for Network Annotation Visualization.Genomics, proteomics & bioinformatics · 2022Article
- Protein-Protein Interaction (PPI) Network of Zebrafish Oestrogen Receptors: A Bioinformatics Workflow.Life (Basel, Switzerland) · 2022Review
- Tracing the footsteps of autophagy in computational biology.Briefings in bioinformatics · 2021Article
- Probabilistic Graphical Models Applied to Biological Networks.Advances in experimental medicine and biology · 2021Article
- A Guide to Conquer the Biological Network Era Using Graph Theory.Frontiers in bioengineering and biotechnology · 2020Review
- Computer aided analysis of disease linked protein networks.Bioinformation · 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
- Data mining and pathway analysis of glucose-6-phosphate dehydrogenase with natural language processing.Molecular medicine reports · 2017Article
- Proteomic signature of muscle fibre hyperplasia in response to faba bean intake in grass carp.Scientific reports · 2017Article
- Empirical Comparison of Visualization Tools for Larger-Scale Network Analysis.Advances in bioinformatics · 2017Review
- Deep interactome profiling of membrane proteins by co-interacting protein identification technology.Nature protocols · 2016Article
- Screening out irrelevant cell-based models of disease.Nature reviews. Drug discovery · 2016Review
- Modelling the Structure and Dynamics of Biological Pathways.PLoS biology · 2016Article
- Computational analysis of protein interaction networks for infectious diseases.Briefings in bioinformatics · 2016Review
- BicNET: Flexible module discovery in large-scale biological networks using biclustering.Algorithms for molecular biology : AMB · 2016Article
- Systematic analysis of the p53-related microRNAs in breast cancer revealing their essential roles in the cell cycle.Oncology letters · 2015Article
- Visualizing genome and systems biology: technologies, tools, implementation techniques and trends, past, present and future.GigaScience · 2015Review
- Computational Prediction of Protein-Protein Interaction Networks: Algo-rithms and Resources.Current genomics · 2013Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundBiological processes such as metabolic pathways, gene regulation or protein-protein interactions are often represented as graphs in systems biology. The understanding of such networks, their analysis, and their visualization are today important challenges in life sciences. While a great variety of visualization tools that try to address most of these challenges already exists, only few of them succeed to bridge the gap between visualization and network analysis.
findingsMedusa is a powerful tool for visualization and clustering analysis of large-scale biological networks. It is highly interactive and it supports weighted and unweighted multi-edged directed and undirected graphs. It combines a variety of layouts and clustering methods for comprehensive views and advanced data analysis. Its main purpose is to integrate visualization and analysis of heterogeneous data from different sources into a single network.
conclusionsMedusa provides a concise visual tool, which is helpful for network analysis and interpretation. Medusa is offered both as a standalone application and as an applet written in Java. It can be found at: https://sites.google.com/site/medusa3visualization.
Identifiers
What OpenQuestion holds
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.