This paper describes the TED Corpus Search Engine (TCSE), an online corpus system that searches transcripts and translations of over 1,800 TED Talks, allowing users to query surface text forms, lemmas, parts-of-speech, or their combinations.
Moreover, structural similarity scores are calculated for the query protein surface residues, and are expressed as different colors on the protein's surface.
We optimize the query and surface that data.
Local structural similarity scores are calculated and mapped to the query protein surface.
The final ensemble of atom-specific, bagging ANNs could then predict the interface atoms of a given query protein surface.
To facilitate the comparison with other methods, all query protein surface residues with structural similarity scores of 7, 8 or 9 are arbitrarily considered to be parts of binding sites.
For all pairs of protein fragments that are accessible to solvent and ligand fragments, the spatial distributions are mapped on the query protein surface, by superimposing the protein fragments for the three representative atoms (Supplementary Table S1).
It's also built a mobile app and is working to integrate with Slack — environments where you don't have time to fiddle with a bunch of different filters or browse a bunch of different pages, so a search product needs to understand complex queries and surface the most important information from documents.
It's also built a mobile app and is working to integrate with Slack — environments where you don't have time to fiddle with a bunch of different filters or browse a bunch of different pages, so a search product needs to understand complex queries and surface the most important information from documents.
Structural similarity scores are calculated for the query protein's surface residues, and are expressed as different colors on the query protein surface.
