Sentence examples for generated and categorized from inspiring English sources

Exact(3)

We have chosen to set up the TILLING platform on M82 mutant collection for which phenotypic data based on visual characterization of M2 plants from young seedling to fruit maturation stages were generated and categorized into a morphological catalogue that can be searched and accessed via the web ([42]; http://zamir.sgn.cornell.edu/mutants/).edu/mutants/

MQY and LE generated and categorized the promoter data set.

Qualitative data were analyzed using latent content analysis whereby themes were generated and categorized according to study questions, objectives and responses.

Similar(57)

Further work is required to test whether killer whales use subunits to generate and categorize their vocal repertoire.

In our previous studies, total 108 mouse MAbs against BP and/or BM have been generated, characterized, and categorized into 8 groups (from A to H) on their binding patterns against a panel of 11 species of the Burkholderia bacteria and the reactive antigens [PS, LPS, and (glyco proteins] recognized by each MAb [16], [17].

The monitored data stems both from synthetically generated workload categorized in different workload volatility classes and from a real-world scenario: scientific workflow applications in bioinformatics.

Due to the highly skewed distribution of the continuous ADDQoL score, a binary ADDQoL variable was generated, which categorized patients into those reporting a negative ('1'), or no/positive impact of diabetes ('0'); the range of the continuous ADDQoL score values at 1 year was -9 to -0.07 ('1') and 0 to 1.15 ('0'), and -7.36 to -0.07 ('1') and 0 to 0.23 ('0') at 5 years.

The process generated 38 codes, which were further interpreted and categorized into eight descriptive codes.

vii) Family wealth index was generated using household materials, monthly salary and household assets, and categorized into quintiles as: lowest, low, middle, high and highest.

To generate the enhanced depth map, the values are sorted and categorized to N uniformly spaced layers.

A dichotomous variable was generated to categorize cases according to their initial symptoms and disease history, which were classified as either bulbar onset (difficulties in facial function or swallowing as an initial symptom) or spinal onset (voluntary muscle fatigue as initial symptoms).

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