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The model uses knowledge based logic and equations combined with a process database to determine the appropriate ground processes and their duration, allowing the estimation of operational measures of performance such as labor, cycle time, and flight rate.
These genes were classed according to 8 biological functions with reference to the GO process database.
I. Indicator selection process Database selection: After evaluating all databases, the most relevant ones were selected as explained above.
The KEGG gene sets, biological process database (c2.KEGG.v4.0) from the Molecular Signatures Database Msig DB (http://www.broad.mit.edu/gsea/msigdb/index.jsp), were used for enrichment analysis.
In particular, a large majority of NO down-regulated genes annotated specifically to the cell cycle (21/38, as annotated in the GO Biological Process database; P = 0.0001).
Using the "biological process" database 272 proteins could be classified from which 175 were associated with metabolism, 55 with cell growth and/or maintenance, 18 with cell communication, 15 with response to external stimulus and 9 with developmental processes.
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In addition, XSLT is used to define processing rules for databases so that only a general processor is required to process databases of different schemata.
Coupling involving only two or three attributes can be handled by construction of suitable task-specific process databases.
The study selection process, databases searched, and references identified are given in Fig. 1.
Among the pathway and process databases, GO has the highest coverage for our gene set (88%) compared to KEGG (38%) and Reactome (35%).
The list of differentially expressed genes in each module was correlated to signaling pathway and cellular process databases to determine if specific physiological processes were associated with particular modules (see Methods).
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