![]() And, while next generation sequencing technology provides annotators with significantly more information, this, perhaps paradoxically, actually increases the need for manual review because there are more biological data points to assess and integrate. Technical advances have made sequencing faster and cheaper, thereby democratizing genome-scale sequencing and allowing a rapidly growing number of researchers to launch sequencing projects ranging from population, to evolutionary, to phenotype, to disease, to classroom projects across a huge spectrum of organisms. ![]() Unfortunately, while this model of a central biocuration team is considered the gold standard for genome annotation, it scales poorly. ![]() For example, the HAVANA team uses their in-house genome editor (Otterlace ) to manually annotate, and then the improved annotations are fed back into the Ensembl pipeline during subsequent quarterly runs. The amended predictions are subsequently used either as training sets or as empirical standards whose alignments are used to improve prediction software's accuracy. The Human and Vertebrate Analysis and Annotation (HAVANA) team at the Sanger Institute manually annotates the human, mouse, and zebrafish genomes. The Model Organism Databases (MODs) often include staff members (that is, biocurators) who review and amend the gene structures. The genome sequencing and annotation paradigm typically involved a large, national genome center that undertook the raw sequencing in coordination with gene prediction pipelines and subsequent manual curation (for example, RefSeq, Ensembl, FlyBase, Wormbase, Saccharomyces Genome Database, The Arabidopsis Information Resource, and Mouse Genome Informatics ). The desktop version of Apollo, Artemis, and FMAP are all examples of such tools. Among these are a small number of more sophisticated genome 'editors' which allow users to go beyond passive viewing to interactively modifying and refining precise locations and structures of genome functional elements. The multitude of genome browsers in genomics all grew out of the need to 'see' the full array of predictions and alignments, their relative positions and their component parts.
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