ArticleBMC systems biology2009
SNAVI: Desktop application for analysis and visualization of large-scale signaling networks.
Article in BMC systems biology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 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
13 citing papers in PubMed.
- Regulatory consequences of neuronal ELAV-like protein binding to coding and non-coding RNAs in human brain.eLife · 2016Article
- DYVIPAC: an integrated analysis and visualisation framework to probe multi-dimensional biological networks.Scientific reports · 2015Article
- Transcription factor and microRNA-regulated network motifs for cancer and signal transduction networks.BMC systems biology · 2015Article
- DAWN: a framework to identify autism genes and subnetworks using gene expression and genetics.Molecular autism · 2014Article
- Article
- Expression2Kinases: mRNA profiling linked to multiple upstream regulatory layers.Bioinformatics (Oxford, England) · 2012Article
- Delineation of key regulatory elements identifies points of vulnerability in the mitogen-activated signaling network.Genome research · 2011Article
- Recovering protein-protein and domain-domain interactions from aggregation of IP-MS proteomics of coregulator complexes.PLoS computational biology · 2011Article
- Introduction to network analysis in systems biology.Science signaling · 2011Article
- Systems biology--biomedical modeling.Science signaling · 2011Review
- Article
- Article
- STATus and Context within the Mammalian Nervous System.Molecular medicine (Cambridge, Mass.)Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
backgroundStudies of cellular signaling indicate that signal transduction pathways combine to form large networks of interactions. Viewing protein-protein and ligand-protein interactions as graphs (networks), where biomolecules are represented as nodes and their interactions are represented as links, is a promising approach for integrating experimental results from different sources to achieve a systematic understanding of the molecular mechanisms driving cell phenotype. The emergence of large-scale signaling networks provides an opportunity for topological statistical analysis while visualization of such networks represents a challenge.
resultsSNAVI is Windows-based desktop application that implements standard network analysis methods to compute the clustering, connectivity distribution, and detection of network motifs, as well as provides means to visualize networks and network motifs. SNAVI is capable of generating linked web pages from network datasets loaded in text format. SNAVI can also create networks from lists of gene or protein names.
conclusionSNAVI is a useful tool for analyzing, visualizing and sharing cell signaling data. SNAVI is open source free software. The installation may be downloaded from: http://snavi.googlecode.com. The source code can be accessed from: http://snavi.googlecode.com/svn/trunk.
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.