I found an oldish paper on this topic (from 1994). Here's a summary:
Determination of the optimal aligned spacing between the Shine-Dalgarno sequence and the translation initiation codon of Escherichia coli mRNAs. by Chen, Bjerknes, Kumar, & Jay. Nucleic Acids Research. (1994)
The authors constructed a series of synthetic RBS regions that ...
The techniques used to do this are ChIP-seq and ChIP-chip.
let the pathogen bind to the (highly replicated) DNA
cut up the DNA into little random pieces by sonication
enrich (“pull down”) the pathogen-bound DNA fragments by using a known antibody which binds to the pathogen
sequence the thus enriched DNA
map the sequenced fragments back to ...
This is true of all protein binding as well as the special case of enzyme-substrate interaction:
Various proteins are more dynamic than others: some have only one or two overall conformations and are relatively implastic otherwise. An example would be a receptor tyrosine kinase like Kit (or CD117, or Mast Stem Cell Growth Factor Receptor, whatever you want ...
That really depends on your system. At least for yeast the difference influences the strength of the activation ("Analysis of Transcriptional Activation at a Distance in Saccharomyces cerevisiae").
For bacteria such long distance regulations have recently been identified. Before that it was thought that this does happen only in eukaryotes. See the paper: "...
ChIP-exo does seem to be the "ChIP-seq killer." I've seen Dr. Pugh present it a few times, and the audience is pretty much always impressed.
One thing I'd do if I were of the "experimental bent" would be to add random degenerate barcodes in the library prep to control for potential PCR artifacts. I imagine that since the "peaks" in ChIP-exo seem to be quite ...
Both models are true depending on how you frame the mechanisms of catalysis. As mentioned by @Blues, proteins are highly dynamic. In that manner, a protein will adopt both the unbound active state shown in the induced fit model and the complementary shape shown in the lock and key model.
(apologies since this is the only figure that I could find to explain ...
I would link your data with the ENCODE dataset. This dataset provides locations of TFBS. It is also accessible via the UCSC genome browser.
For the actual question TFBS are located pretty much everywhere, including exons (as described here), introns and of course intergenic regions (e.g. enhancers, silencers, control locus regions - here a reference).
I don't have a definitive answer, but I can perhaps offer some insight. Given the necessary function of rpoA, I would be willing to bet that SigA is the factor responsible for its transcription, so I will focus my discussion there.
Predicting promoters without experimentation can be very challenging given their immense variability. The idealized core ...
The processes are called gene rearrangement and somatic hypermutation, and are used by maturing B-cells to generate very (very) large amounts of diversity in the antibody repertoire. If your institution has access, this great article in Annual Reviews in Immunology has all the details, or you can read about it in Janeway (slightly outdated edition). ...
A colleague of mine discovered the cipher that determines TAL effector DNA specificities, which is described in this short paper. These specificities were determined by observing TAL effectors bound to DNA and recording how often a given repeat-variable diresidue (RVD) would correspond to a given nucleotide (using a weight matrix).
Now that the ...
Nucleotide-associated proteins are DNA-binding proteins that bind DNA. RNA-polymerase associated proteins bind RNA-polymerases and are required for its functionality.
In more detail:
DNA-binding protein is a higher level term that comprises all proteins that bind to DNA. These can be seen as nucleotide-associated proteins as they interact with ...
Neither of the terms “Nucleotide-associated protein” or “RNA-polymerase associated protein” are standard in molecular biology in so far as they are not defined in the reference Gene Ontology. (In contrast, “DNA-binding” is.)
An internet search does not bring up many examples of the former usage (at least) and in those it brings up it is not defined. One ...
This isn't a question with a really well accepted answer yet, and comes up quite a lot in e.g. studies of population variation in transcription factor motifs.
Usually, we approximate the sequence preferences of a DNA-binding protein with a position weight matrix. A weight matrix will given you a score for two sequences, so the simplest means of quantifying ...
In addition to the 4 nucleotide letters, there are letters that mean "the letter is one of these two or three:
M = aMine = A or C
R = puRine = A or G
W = Weak (two hydrogen bonds) = A or T
S = Strong (three hydrogen bonds) C or G
Y = pYrimadine = C or T
K = Ketone = G or T
B = not A
D = not C
H = not G
U = not T
I would guess the the lowercase ...
I agree it can be extremely confusing sometimes to find the right data.
Do you know RSAT (Regulatory Sequences Analysis Toolkit) ?
If you go in "help & contact", and "motif databases", you'll find the Yeastract database: http://rsat-tagc.univ-mrs.fr/rsat/motif_databases/Yeastract/
I thought it would also be on JASPAR, but couldn't find it.
Then for ...
As it seems with about everything in protein science, the answer is it depends on the protein. Many proteins will lose activity if they are truncated; however, I've worked with GPCR's that were truncated down to the extracellular portion only and they showed consistent kinetic results. Antibodies have been cut into pretty tiny chunks (scFv's) to create ...
Antibody molecules or immunoglobulins (Ig) consist of heavy and light chains (e.g. two of each in IgG). Both heavy and light chains have variable domains at their N termini.
During development of the immune system the pro-B cells in the bone marrow undergo gene segment rearrangements, bringing V and J segments together for Ig light chain production, and V,D ...