Sentence examples for binding knowledge from inspiring English sources

CHIF, the knowledge-based interaction fingerprint scoring by Mpamhanga et al. [14], combines similarity coefficients with the scores of Goldscore to yield a binding knowledge modified score [14].

Here we introduce the major classes of sequence- and structure-specific RNPs, and discuss aspects of RNA secondary structure that impact RBP binding; knowledge of how proteins interact with RNA is important for the interpretation of high-throughput data.

In this chapter, we review recent advances in computational work for modular domain phosphopeptide binding and knowledge gained for their binding mechanisms.

Although there are many studies of A·T specific minor groove binding, our knowledge of minor groove binders with mixed A·T/G·C bp sequences is mostly limited to polyamides.

For example, it may be possible to use ligand binding site knowledge to limit the search only to fragments proximate to the binding site, and to alter the smoothing associated with such focused studies.

In the first set of experiments we extract the binding-relevant knowledge used to extend the structural similarity measures by literature review and support the process by MCS similarity ranking and docking calculations.

Restriction of the search to a primary binding site requires knowledge of its location and also neglects multiple sites such as allosteric ones [7, 8].

Our study shows that adding binding relevant background knowledge can lead to significantly improved similarity rankings in virtual screening and that even basic data mining approaches can lead to competitive results making hand-selection of the background knowledge less crucial.

Information on the target pharmacology, in particular its expression and turnover, drug-target binding kinetics, and knowledge of the fate of drug-target complexes, are generally required to build a mechanistic model.

Only few studies have focused on Cry4Aa toxin binding to our knowledge [ 52, 53] and nothing is known about its potential membrane receptors.

The second guiding idea in constructing the platform is the need to integrate functional data (gene expression), regulatory events data (epigenomics, TF binding) and the knowledge base (lists of functionally related genes).