ArticleBMC bioinformatics2009
JNets: exploring networks by integrating annotation.
Article in BMC bioinformatics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed.
- Network controllability analysis of intracellular signalling reveals viruses are actively controlling molecular systems.Scientific reports · 2019Article
- HIV-1, human interaction database: current status and new features.Nucleic acids research · 2015Article
- Structure and dynamics of molecular networks: a novel paradigm of drug discovery: a comprehensive review.Pharmacology & therapeutics · 2013Review
- GPS-Prot: a web-based visualization platform for integrating host-pathogen interaction data.BMC bioinformatics · 2011Article
- Patterns of HIV-1 protein interaction identify perturbed host-cellular subsystems.PLoS computational biology · 2010Article
- NAViGaTOR: Network Analysis, Visualization and Graphing Toronto.Bioinformatics (Oxford, England) · 2009Article
- Network analyses in systems pharmacology.Bioinformatics (Oxford, England) · 2009Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
backgroundA common method for presenting and studying biological interaction networks is visualization. Software tools can enhance our ability to explore network visualizations and improve our understanding of biological systems, particularly when these tools offer analysis capabilities. However, most published network visualizations are static representations that do not support user interaction.
resultsJNets was designed as a network visualization tool that incorporates annotation to explore the underlying features of interaction networks. The software is available as an application and a configurable applet that can provide a flexible and dynamic online interface to many types of network data. As a case study, we use JNets to investigate approved drug targets present within the HIV-1 Human protein interaction network. Our software highlights the intricate influence that HIV-1 has on the host immune response.
conclusionJNets is a software tool that allows interaction networks to be visualized and studied remotely, from within a standard web page. Therefore, using this free software, network data can be presented in an enhanced, interactive format. More information about JNets is available at http://www.manchester.ac.uk/bioinformatics/jnets.
Indexed as
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.