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The inverse problem of designing processing stages that lead to a desired texture or texture-dependent property is addressed by mining a database of orientation distribution functions (ODFs).
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A few examples of targeted questions potentially answerable by mining the database include: a) the association of resuscitative fluids and AKI, b) delineation of predictive and associated factors between transient versus persistent AKI, c) the independent outcomes of fluid overload and oliguria in all critically ill patients, and the d) associations and outcomes of subclinical-AKI.
In addition, we tested a set of "antioxidant response element genes", which included 37 human genes that have bona fide NRF2 binding sites (or antioxidant response elements), curated by mining PubMed database [9].
29 Criteria were assessed by mining various database sources to populate criteria-specific gene lists.
By mining our annotation database, we found a diverse set of candidate genes for future genomic studies related to life in extreme environments (Table 3).
The text mining similarity is computed by mining the curated database, such as OMIM and MEDLINE, using a co-occurrence scheme and a natural language processing approach (Jensen et al., 2006; Šarić et al., 2006).
All intranasal/sinus cultures obtained by otolaryngologists at Stanford over a 20-year period (1990 2010) were retrospectively reviewed by mining the microbiology database.
Three distinct NLR subfamilies were identified by mining genome databases of various non-mammalian vertebrates; the first subfamily (NLR-A) resembles mammalian NODs, the second (NLR-B) resembles mammalian NALPs, while the third (NLR-C) appears to be unique to teleost fish.
Therefore, it would be theoretically feasible to engineer metabolic processes quantitatively by mining enzymatic kinetic database.
To gain insight into the comprehensive roles of the OsOPT family members in response to various stresses, their expression patterns were investigated in rice seedlings subjected to abiotic (salt, drought and cold) (Figure 5) and biotic (two rice diseases) stresses (Figure 6) by mining the MPSS database.
Candidate genes for QTL support intervals were identified by mining the SNP database on GeneNetwork (http://genenetwork.org/webqtl/main.py?FormID=snpBrowser) for mis/non-sense polymorphisms between B6 and D2 strains within exons of genes within support intervals and by PolyPhen analysis (http://coot.embl.de/PolyPhen/).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com