With microarray experiments I got a list of about 100 transcription factors differentially expressed. I would like to give my list biological significance. Are there any tools or databases that can automatically classify the TF in my list and give them some biological sense?
You can find biological meaning of proteins with their GO (gene ontology) terms. You can look at interproscan and/or biomart. I guess that Interpro-biomart (biomart search of interproscan databases) could be useful in your case : http://www.ebi.ac.uk/interpro/biomart/martview/e14c3ad39409d40370a4af04397c4622
I suspect that in your dataset, the transcription factor that you find to be differentially regulated may have in part common targets. I do not know of a good tool to directly connect transcription factors to their target genes, which anyway depend on tissue type and experimental conditions, but I would try a pathway analysis tool like DAVID or Enrichr, looking for common downstream effectors.
It depends in part on the organism - if your organism has a lot of published transcriptome data, you could try to cluster all available expression arrays, and see which other genes are in the same clusters as your transcription factors. This would not be a definitive answer but if you tested these clusters for enriched biological annotations it would suggest some hypotheses for which processes your transcription factors are involved in. If you are working in a model organism there might be some geentic evidence published that tell which genes are downstream targets of your transcription factors - you could search in BioGrid as a start.
If your laboratory has a subscription, Biobase and Transfac is a good resource. As well as, Ingenuity Pathway Analysis. Transfac has non-proprietary database access, but I haven't used it. I also agree with biomaRt as an excellent resource.
DAVID has a transcription factor binding site database that lists specific protein-protein interactions
Your experiment most likely generated not only a list of TFs but also of other regulated genes. Therefore one would expect that the interesting TFs are those that actually regulate the genes observed. In order to detect common TF binding sites among the genes you find regualted you might wish to use oPOSSUM (http://opossum.cisreg.ca/oPOSSUM3/). Focus on those TFs that are regulated and have potential binding sites in the promoters of the genes regulated.
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