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Despite more domains being defined manually for a single chain in contrast to automated methods, manual definition produced a marginally lower number of polypeptide segments per domain (fig 2b).
However, a manual definition of proper and application-specific process templates is very challenging.
Fields were automatically detected by algorithms to avoid the time consuming manual definition of field boundaries.
However, landscape scale studies require large data sets, making manual definition of spatial neighbourhoods problematic.
This factor can be calculated by the following example: the manual definition of one job takes 3 min.
Structural correspondence learning depends on the manual definition of pivot functions that capture correspondence between the source and target domains.
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A distinct rhetorical armature surrounds that core of field manual definitions, statistical studies and direct testimony.
For example, the solutions defined for Prettenhofer [91] and Wei [125] require manual definitions of source and target correspondence.
PDP performed close to manual definitions, however, with less number of domains per chain (fig 2a PDP).
For analysis of domain size, our manual definitions were comparable to PDP, SCOP and CATH in the percentage of defined domains ranging between 95 and 215 residues in length, with DOMAK shifting towards longer domains (fig 2c).
We defined at least two domains for every chain in the multi-domain proteins class (fig 2a by structure), with the number of domains defined per chain falling gradually from 2 to 6. Manual definitions also split 13 chains into 7 or more domains, and are mostly proteins involved in replication and transcription, notably polymerases.
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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