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Functional annotation of genes requires a controlled vocabulary (or ontology) to name the predicted functional features. However, because there are numerous ways to define gene functions, the annotation process may be hindered when it is performed by different research groups.
Knowledge base annotation is done based on the information of gene attribute, protein function and its metabolism. In this type of annotation more emphasis is given to genetic variation that disrupts the protein function domain, protein-protein interaction and biological pathway.
The Gene Ontology (GO) is a major bioinformatics initiative to unify the representation of gene and gene product attributes across all species. [1] More specifically, the project aims to: 1) maintain and develop its controlled vocabulary of gene and gene product attributes; 2) annotate genes and gene products, and assimilate and disseminate annotation data; and 3) provide tools for easy access ...
A simple gene prediction algorithm for prokaryotes might look for a start codon followed by an open reading frame that is long enough to encode a typical protein, where the codon usage of that region matches the frequency characteristic for the given organism's coding regions. [5]
Ab Initio gene prediction is an intrinsic method based on gene content and signal detection. Because of the inherent expense and difficulty in obtaining extrinsic evidence for many genes, it is also necessary to resort to ab initio gene finding, in which the genomic DNA sequence alone is systematically searched for certain tell-tale signs of protein-coding genes.
Especially, gene-based annotation will highlight the exact amino acid change if the mutation is in the exonic region and the predicted effect on the function of the known gene. This approach is useful for identifying variants in known genes from Whole Exome Sequencing data.
One option is manual annotation, whereby a team of scientists tries to locate genes using experimental data from scientific journals and public databases. However this is a slow, painstaking task. The alternative, known as automated annotation, is to use the power of computers to do the complex pattern-matching of protein to DNA.
Each gene can be described (annotated) with multiple terms. The GO is actively used to classify genes from humans, model organisms and a variety of other species. Using the GO, it is possible to retrieve the set of terms used to describe any gene, or conversely, given a term, return the set of genes annotated to that term.