T-profiler statistics

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Citations per year

Number of citations per year for the bioinformatics software tool T-profiler

Tool usage distribution map

This map represents all the scientific publications referring to T-profiler per scientific context
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Associated diseases

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chevron_left Gene set enrichment analysis Differential expression detection chevron_right
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T-profiler specifications


Unique identifier OMICS_18763
Name T-profiler
Interface Web user interface
Restrictions to use None
Input data A microarray data.
Input format TSV
Computer skills Basic
Stability Stable
Maintained Yes


  • Plants and Fungi
    • Candida albicans
    • Saccharomyces cerevisiae


  • person_outline Harmen J. Bussemaker

Publication for T-profiler

T-profiler citations


Deconvolution of Transcriptional Networks in Post Traumatic Stress Disorder Uncovers Master Regulators Driving Innate Immune System Function

Sci Rep
PMCID: 5670244
PMID: 29101382
DOI: 10.1038/s41598-017-15221-y

[…] regulators (pleiotropy) for computing the enrichment of a protein regulon in differentially expressed genes. The main advantage of VIPER compared to the other gene enrichment analysis methods such as T-profiler, Fisher’s exact test, and gene set enrichment analysis (GSEA) is that it uses a fully probabilistic enrichment analysis framework, supporting seamless integration of genes with different li […]


Evaluating Transcription Factor Activity Changes by Scoring Unexplained Target Genes in Expression Data

PLoS One
PMCID: 5056719
PMID: 27723775
DOI: 10.1371/journal.pone.0164513

[…] emoving all regulations of the TF from F. The difference between the normal and the knockout model is used to calculate a z-score that indicates how important the respective TF is for the experiments.T-profiler [] performs a t-test between the fold changes of the genes that are targets of a TF and all other genes. To account for overlaps in the target sets of the TFs, the method iteratively select […]


Comparative Transcriptome Analysis Reveals That Lactose Acts as an Inducer and Provides Proper Carbon Sources for Enhancing Exopolysaccharide Yield in the Deep Sea Bacterium Zunongwangia profunda SM A87

PLoS One
PMCID: 4332637
PMID: 25679965
DOI: 10.1371/journal.pone.0115998

[…] the EPS gene cluster were up-regulated two-fold or higher at day 6. Polysaccharide biosynthesis and export proteins (ZPR_0546, ZPR_0566 and ZPR_0567) were also up-regulated at day 6. Tested with the T-profiler method, the EPS gene group had a higher mean expression level than that of all of the other genes in the SM-A87 genome at days 4 and 6 (p<0.02 and p<0.001 for days 4 and 6, respectively). T […]


Global Genome Response of Escherichia coli O157∶H7 Sakai during Dynamic Changes in Growth Kinetics Induced by an Abrupt Temperature Downshift

PLoS One
PMCID: 4057180
PMID: 24926786
DOI: 10.1371/journal.pone.0099627

[…] old at 30 mins (pstSCA, cysPUWA, cysZ, gntU), 90 mins (arsB, pstSCAB, cysPUWA, cysZ, gntU), 160 mins (arsB, pstSCAB, cysPUWA, gntU) and 330 mins (arsB, pstSCA).Negative regulation was observed in the T-profiler analysis for genes involved in the transport of carbohydrates, organic alcohols and acids at 30, 90 and 330 min (Table S2 in ). The majority of those genes with greater than a 1-log2 fold r […]


Time course gene expression profiling of yeast spore germination reveals a network of transcription factors orchestrating the global response

BMC Genomics
PMCID: 3577491
PMID: 23066959
DOI: 10.1186/1471-2164-13-554

[…] T-profiler [] was used to identify TFs and upstream consensus motifs. This online tool (http://www.t-profiler.org) compares the mean expression ratios of groups of genes, and all genes within each gro […]


Yeast IME2 Functions Early in Meiosis Upstream of Cell Cycle Regulated SBF and MBF Targets

PLoS One
PMCID: 3290606
PMID: 22393365
DOI: 10.1371/journal.pone.0031575
call_split See protocol

[…] IAME compliant and have been deposited into the Gene Expression Omnibus (GEO) database (http://www.ncbi.nlm.nih.gov/geo/), series identifier GSE26649. Consensus motif analysis was performed using the T-Profiler tool (http://www.t-profiler.org/) and MatrixREDUCE (default settings) developed by Harmen Bussemaker and colleagues (Columbia University), and the MUSA algorithm available through the Ye […]

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T-profiler institution(s)
Swammerdam Institute for Life Sciences–Microbiology, University of Amsterdam, Biocentrum Amsterdam, Amsterdam, Netherlands; Department of Biological Sciences, Columbia University, New York, NY, USA; Center for Computational Biology and Bioinformatics, Columbia University, New York, NY, USA
T-profiler funding source(s)
Supported by grants from the Netherlands Foundation for Technical Research (STW) (APB.5504) and from the National Institutes of Health to (R01HG003008).

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