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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

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

[…] 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 […]


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

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

[…] in expression levels of all genes for each time point. additional applications were employed for the downstream analysis of the expression data, these applications are described below., 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 […]


Gene set analyses for interpreting microarray experiments on prokaryotic organisms

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

[…] 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 [] […]

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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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