Sentence examples for classical annotation from inspiring English sources
The resulting workflow leads to the annotation of a yeast genome in 5 to 7 hours compared to the use of classical annotation tools which take 70 to 80 hours to annotate such a genome.
In cases where the genome of the organism is sequenced and a well annotated closely related genome exists, it is unlikely that our method can improve upon the classical annotation approach based on the identification of all orthologous genes.
Alternative approaches to metabolic network reconstruction bypass the classical annotation step altogether, taking instead advantage of the curated links between enzyme-encoding gene sequences and reactions [or EC numbers, as in the Genome-Based Modeling (gem) system (Arakawa et al., 2006)] provided by some metabolic databases.
Unlike classical tissue annotation and clinical data, these high-throughput techniques generate a large amount of well formatted data, typically for a relatively small number of tissue specimens.
Most classical gene annotation methods exclude short ORFs (Basrai et al. 1997) because they often appear by chance alone and do not code for proteins.
The search for candidate genes for orphan metabolic activities is in some ways the reverse of the classical genome annotation problem (i.e. searching the function of identified genes).
Interestingly, by classical genome annotation, the Chloroflexi bacteria, as well as certain other archaeal and bacterial groups, contain only a subset of components of the classical (PMK-, MDD-utilizing) alternativetive (MPD-, IPK-utilizing) MVA pathways, resulting in what appears to be the existence of two incomplete branches of the MVA pathway in one organism.
The classical approach to the annotation of protein functions is based on sequence similarity using BLAST (Altschul et al., 1997) or similar programs.
Full automation was achieved combining the classical 'hard' rule-based annotation with the modern comprehensive character extraction along with model-free clustering.
The FASTER algorithm thereby absorbs the individual variance as much as possible in the character extraction and clustering steps to safely adopt the classical 'hard' rule in annotation step.
