Editing Gene prediction (section)

=== Multiple informants ===

TWINSCAN examined only human-mouse synteny to look for orthologous genes. Programs such as N-SCAN and CONTRAST allowed the incorporation of alignments from multiple organisms, or in the case of N-SCAN, a single alternate organism from the target. The use of multiple informants can lead to significant improvements in accuracy.<ref name=":0" />

CONTRAST is composed of two elements. The first is a smaller classifier, identifying donor splice sites and acceptor splice sites as well as start and stop codons. The second element involves constructing a full model using machine learning. Breaking the problem into two means that smaller targeted data sets can be used to train the classifiers,
and that classifier can operate independently and be trained with smaller windows. The full model can use the independent classifier, and not have to waste computational time or model complexity re-classifying intron-exon boundaries. The paper in which CONTRAST is introduced proposes that their method (and those of TWINSCAN, etc.) be classified as ''de novo'' gene assembly, using alternate genomes, and identifying it as distinct from ''ab initio'', which uses a target 'informant' genomes.<ref name=":0" />

Comparative gene finding can also be used to project high quality annotations from one genome to another. Notable examples include Projector, GeneWise, GeneMapper and GeMoMa. Such techniques now play a central role in the annotation of all genomes.