The phrase "automated functional" is correct and usable in written English.
It can be used in contexts related to technology, software, or processes that are designed to operate automatically and perform specific functions.
Example: "The new software includes an automated functional module that streamlines data processing."
Alternatives: "automated feature" or "automated capability".
To fill the gap between the number of sequences and their (quality) annotations, we need fast, yet accurate automated functional annotation methods.
The p.G613A, however, present in the N-terminal helical bundle of VPS9, is not conserved even in mouse RIN3, and is likely to be a neutral substitution consistent with data from automated functional prediction tools (Functionality score = 1; Table 1).
The remaining species-specific proteins, which represented 4.8-10.74.8-10.7%genomes (Additional file 16: Table S8) had very few predicted functions since 93.6-97.8% of them had no automated functional annotations.
Results indicate that the proposed method is suitable for automated functional testing of embedded control systems within a Software-in-the-Loop test environment.
Quantification was done using BRASS fully automated functional brain analysis (Hermes, Sweden).
Designed to be analogous to the Gene Ontology (GO) system, CO was one of the first open-source, automated functional group ontologies to be formalized.
More recently, we reported on the development of nanowire substrate-enabled laser scanning cytometry (LSC) for cell analysis in order to achieve quantitative, automated, and functional evaluation of the circulating tumor cells where the captured rare cells were at the very early stage of incubation (<0.5 h)[6].
Here we present a novel automated protein functional assignment method based on the neural response algorithm [ 28].
We designed a novel automated protein functional assignment method based on the neural response algorithm, which simulates the neuronal behavior of the visual cortex in the human brain.
Hari Krishna Yalamanchili et al. designed a novel automated protein functional assignment method based on the neural response algorithm, which simulates the neuronal behavior of the visual cortex in the human brain, to fill the gap between the number of sequences and their annotations.
Automating protein functional annotation is an important and difficult problem in computational biology.
