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Using some of the same methods we discussed a few months ago, you can watch your favorite sport—I'll be watching football (soccer) from the many watering holes in and around Barcelona as it happens, in real time.
All the other methods we discussed can only discover nonpseudo-knotted motifs.
Most of the alignment based methods we discussed discover motifs based on both sequence and structure similarity.
Most methods we discussed here searched for motifs whose occurrences were contiguous subsequences of the input sequences.
And as opposed to the other methods we discussed, one cannot assign a stand-alone value to a country.
The genetic programming-based methods we discussed discover motifs as a sequence of segments which are either single stranded or complementary, with a bound (upper and lower) constraint on their lengths.
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We do this from (a) a conceptual and theoretical perspective so that you truly understand the methods we discuss, and ultimately (b) so that you feel appropriately and completely comfortable using these methods in your own work.
The computational methods we discuss range from de novo methods, which identify structural elements in an EM map, to structure fitting methods, where known high resolution structures are fit into a low-resolution EM map.
After presenting the models and methods, we discuss empirical evidence on the performance of the methods.
These challenges can be addressed using the methods we discuss in this section.
In section Exploratory methods we discuss unsupervised methods (component based models and clustering methods).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com