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Although the best evaluation is still performed by a human expert, we find approaches that define metrics and evaluation methodologies for automatic and in-depth evaluation.
In this context, novel paradigms, models and methodologies for automatic annotation must be investigated.
The unforgiving pace of growth of available biological data has increased the demand for efficient and scalable paradigms, models and methodologies for automatic annotation.
Considering that the predominantly used methodologies for automatic genome annotation (sequence similarity) have the low-complexity filter enabled as a default setting and matrices that are used as training dataset proteins with different composition profiles (most are globular proteins), our results suggest that this approach is inefficient for the functional annotation of disordered proteins.
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A methodology for automatic subsampling matrix design was also developed.
In Section 3, the proposed methodology for automatic aligning industrial images is introduced.
In this paper, we propose a novel methodology for automatic pattern classification of pathological voices.
In the paper, the authors illustrate a methodology for automatic threshold calculations in a large monitoring system.
AIDA-C consists of an innovative layout-aware optimization-based methodology for automatic sizing of analog ICs.
We present a methodology for automatic corrosion detection in digital images of carbon steel storage tanks and pipelines from a petroleum refinery.
This paper presents a semi-supervised methodology for automatic recognition and classification of elderly activity in a cluttered real home environment.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com