Reporter assay using the beta-galactosidase (lacZ) gene. The lacZ gene is typically fused to the promoter of interest. Differential regulation of the promoter mediated by the TF is assessed by induction of the system and evaluation of lacZ expression. Bacteria expressing lacZ appear blue when grown on a X-gal medium. The assay is often performed using a plasmid borne construction on a lacZ(def) strain.

The DNAse foot-printing method starts by focusing on a given region of interest (e.g. a promoter region) and amplifying it by PCR to obtain lots of sample. It then throws in the TF and then the DNAse. The mix is left to stir for a short time and then gel electrophoresis is run to compare the pattern of fragments in a control (no TF) and in the sample. If the TF has bound the sample, it will have protected a stretch of DNA (encompassing some fragments of the control) and thus those fragments will not appear in the sample gel. The fragments can then be cut-out from the gel, purified and sequenced to obtain the sequence of the protected region. This is often used to identify the binding motif of a TF for the first time. The foot-printing will typically resolve the protected region down to 50-100 bp, and the sequence can be then examined for possible TF-binding sites either by eye of using a computer search.

Electro-mobility shift-assays (or gel retardation assays) are a standard way of assessing TF-binding. A fragment of DNA of interest is amplified and labeled with a fluorophore. The fragment is left to incubate in a solution containing abundant TF and non-specific DNA (e.g. randomly cleaved DNA from salmon sperm, of all things) and then a gel is run with the incubated sample and a control (sample that has not been in contact with the TF). If the TF has bound the sample, the complex will migrate more slowly than unbound DNA through the gel, and this retarded band can be used as evidence of binding. The unspecific DNA ensures that the binding is specific to the fragment of interest and that any non-specific DNA-binding proteins left-over in the TF purification will bind there, instead of on the fragment of interest. EMSAs are typically carried out in a bunch of fragments, shown as multiple double (control+experiment) lanes in a wide picture. Certain additional controls are run in at least one of the fragments to ascertain specificity. In the most basic of these, specific competitor (the fragment of interest or a known positive control, unlabelled) is added to the reaction. This should sequester the TF and hence make the retardation band disappear, proving that the binding is indeed specific

This technique is used to determine precise thermodynamic parameters such as the binding affinity of proteins and DNA. The temperature of two identical cells containing a known concentration of TF is monitored. The ligand (DNA) with a putative site or not is added to the cells in precisely measured aliquots. The difference in temperature observed after adding the ligand, because in one cell it binds to the target while in the other it does not, can be used to compute the energetics of the reaction and therefore the binding affinity of the TF for the DNA fragment.

Once the binding motif for a TF is known, this motif (which essentially defines a pattern) can be used to scan sequences in order to search for putative TF-binding site. This is useful, for instance, when trying to identify TF-binding site in ChIP-chip data. Searching for TF-binding site can be done in numerous ways. The most basic method is consensus search, in sequences are scored according to how many mismatches they have with the consensus sequence for the motif. A more elaborate way of searching involves using regular expressions, which allow to search for more loosely defined motifs [e.g. C(C/G)AT]. Common algorithms for this type of search include Pattern Locator and the DNA Pattern Find method of the SMS2 suite, but also some word processors. Finally, the mainstream way of conducting TF-binding site search is through the use of position-specific scoring matrices, which basically count the occurrences of each base at each position of the motif and use the inferred frequencies to score candidate sites. Algorithms in this last category include TFSEARCH, FITOM, CONSITE, TESS and MatInspector.