Sentence examples for lists extracted from from inspiring English sources

These could include generating intersects and differences with, for example, disease associated protein lists or other target protein lists extracted from public databases.

Finally, after application of rigorous selection criteria, a total of 18 categories (11 GO terms and seven KEGG pathways) were considered as consistently overrepresented in the gene lists extracted from the 23 different GEP studies on CRC prognosis.

We also provide the human, mouse and rat orphan receptor lists extracted from Swiss-Prot.

Confero enables research sites to store and manage analyzed contrast datasets and identifier (ID) lists of interest (e.g. gene lists extracted from research papers, diagnostic gene signatures), automatically compute and store gene sets from these contrast data and ID lists, and analyze data to support biological interpretation.

Additionally, we used hypergeometric tests to annotate for signaling pathways (gene lists extracted from Wormbook, KEGG and Panther), druggable genes [ 33], htt partners [ 7, 34] and genes involved in autophagy, mitochondrial function and synaptic activity (gene lists kindly provided by the CHDI Foundation).

The main finding is that there is a very low degree of agreement among the target lists extracted from the different databases, and only one of the database (MetaCore) can provide a statistically significant overlap of targets when compared to the gold standard lists.

A conventional n-best list extracted from a word-based lattice is also presented in Fig. 8 a for comparison.

To fulfill this objective, a practical study is developed through the application of three traditional cutoff point approaches (absolute, threshold, and relative) to a term list extracted from a corpus.

mSpinning the Election (Skillicorn and Little) "We do not yet completely understand these models of word use, so the results should be taken with a grain of salt [52]." nStopwords list extracted from [53].

The top-list of single and multi-word terms were contrasted firstly against the term list extracted from an open-domain corpus and secondly against a top list of terms acquired from a corpus at the level of the different regulated-domain.

To identify the most relevant terms, a stemming algorithm (Lovins stemmer [ 25 ]) and a stopword list extracted from GATE tool [ 41 ] are used.