FIVA statistics

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Citations per year

Number of citations per year for the bioinformatics software tool FIVA

Tool usage distribution map

This map represents all the scientific publications referring to FIVA per scientific context
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Associated diseases


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FIVA specifications


Unique identifier OMICS_19186
Alternative name Function Information Viewer and Analyzer
Software type Framework/Library
Interface Command line interface
Restrictions to use None
Input data Some transcriptome data and genome annotation files.
Input format EMBL, Genbank
Operating system Unix/Linux, Mac OS, Windows
Programming languages Java
Computer skills Advanced
Stability No
Maintained No


No version available

Publication for Function Information Viewer and Analyzer

FIVA citations


Transcriptional Profile of Bacillus subtilis sigF Mutant during Vegetative Growth

PLoS One
PMCID: 4624776
PMID: 26506528
DOI: 10.1371/journal.pone.0141553

[…] hange higher then 2 and a Bayes p-value lower than 0.05 were considered to be expressed differentially. The gene lists selected with these criteria are presented in and Tables. The software package FIVA (Functional Information Viewer and Analyzer; [] was used to identify overrepresented functional categories in differentially expressed genes. Sources used by this software include: metabolic path […]


Transcription factors and genetic circuits orchestrating the complex, multilayered response of Clostridium acetobutylicum to butanol and butyrate stress

BMC Syst Biol
PMCID: 3828012
PMID: 24196194
DOI: 10.1186/1752-0509-7-120

[…] e butanol (BuOH) versus butyrate (BA) stress responses is essential for understanding the general (that is, the common) stress response as well as the specialized, stressor-dependent responses. Using FIVA (Functional Information Viewer and Analyzer) [], we identified the statistically significant differentially expressed functional categories based on annotated pathways (KEGG database []) and Gene […]


Time Resolved Transcriptomics and Bioinformatic Analyses Reveal Intrinsic Stress Responses during Batch Culture of Bacillus subtilis

PLoS One
PMCID: 3210768
PMID: 22087258
DOI: 10.1371/journal.pone.0027160

[…] The FIVA software was used to perform the functional enrichment analysis on genes from the most expressed fractions at each of the time points. Various annotation sources were used in this enrichment ana […]


Transcriptional Responses of Bacillus cereus towards Challenges with the Polysaccharide Chitosan

PLoS One
PMCID: 3169574
PMID: 21931677
DOI: 10.1371/journal.pone.0024304

[…] ificantly differentially expressed genes with cut-off value ≥3 are shown for the same chitosans. SMART searches were performed to detect different protein domains of the annotated genes.According to FIVA (Functional Information Viewer and Analyzer) analysis , genes involved in ion transport, especially transport of potassium, were found significantly upregulated upon exposure to both chitosans () […]


Gene set analyses for interpreting microarray experiments on prokaryotic organisms

BMC Bioinformatics
PMCID: 2587482
PMID: 18986519
DOI: 10.1186/1471-2105-9-469

[…] y of the non-cutoff based methods are not directly applicable to prokaryotic experiments.There are two web-based software tools focused on prokaryotes, available for conducting gene set analysis. The FIVA tool [] uses FET and a variant of FET proposed by Breitling et al. [] which finds the optimal cutoff for "significant" vs. "non-significant" genes for each gene set. The JProGo tool [] implements […]


Transient heterogeneity in extracellular protease production by Bacillus subtilis

Mol Syst Biol
PMCID: 2387230
PMID: 18414485
DOI: 10.1038/msb.2008.18

[…] fraction (, ‘up') and genes with ratios between 0.5 and 1.6 were not considered to be significantly different between both fractions (, ‘not'). The resulting list was subsequently analyzed using the FIVA software (). Microarray data are accessible from the publicly available Gene Expression Omnibus repository ( under accession number GSE9266. […]

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FIVA institution(s)
Molecular Genetics, Groningen Biomolecular Sciences, Institute for Mathematics and Computing Science and Groningen Bioinformatics Centre, University of Groningen, Groningen, Netherlands
FIVA funding source(s)
Supported by a grant from The Netherlands Organization for Scientific Research and industrial partners in the NWO-BMI project number 050.50.206 on Computational Genomics of Prokaryotes and by Center IOP Genomics; grant QLK3-CT-2001-01473 under the EU programme ‘Quality of life and management of living resources: The cell factory’.

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