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In contrast, we have included a richer environment for practical work on CRISPR: access to extended queries via BLAST parameters, multiple graphical views, etc.
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This research extends query-driven interface research by providing three context-specific design features: timeline based visualizations; visual indications of search relevance and matched keywords; and visual representations of user activity in shared repositories.
Our work extends query-driven interface research by providing two new forms of contextual information to help users understand the set of documents resulting from their query: 1) temporal context, in the form of a timeline to show when each document was created and 2) search-relevance context, by showing exactly which of the entered keywords matched each document.
Instead, we used the fact that Virtuoso can combine SQL and SPARQL queries and designed a preprocessor that translates extended SPARQL queries into SQL/SPARQL.
We also discuss whether the loss functions of existing ranking algorithms can be extended to query-level.
We specifically addressed the long-standing problem of auxin and glucose crosstalk in plant development and extended the query to the possible role of G proteins in this complexity.
It implements and extends Dynamic Queries (Ahlberg et al. 1992) and Visual Information Seeking principles (Ahlberg and Shneiderman 1994).
We can extend this query further: we can add restrictions taken from reference ontologies (e.g., query for sugars that have a phosphorus atom as part; sugars that have an oxoacid as functional parent) or add restrictions arising from the model (e.g., sugars located in a cell; sugars that are the input of biosynthetic processes that have ATP as output).
This article addresses a novel strategy that extends the query optimizer of a DBMS, so that it can also perform both logical and physical query plan optimizations in searches that include similarity predicates.
"Developers will be able to extend [Query Builder] for themselves and extend it for the community," Halstead said.
Indeed, adding new functions, supporting evolutions of the data model, extending the query language and then supporting well adapted optimization strategies, can require important coding effort.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com