Sequence database

Searching in a sequence database involves looking for similarities between a genomic/protein sequence and a query string and, finding the sequence in the database that "best" matches the target sequence (based on criteria which vary depending on the search method). The number of matches/hits is used to formulate a score that determines the similarity between the sequence query and the sequences in the sequence database. The main goal is to have a good balance between the two criteria. == History ==

1950 The need for sequence databases originated in 1950 when Frederick Sanger reported the primary structure of insulin. He won his second Nobel Prize for creating methods for sequencing nucleic acids, and his comparative approach is what sparked other protein biochemists to begin collecting amino acid sequences. Thus marking the beginning of molecular databases. 1960 In 1965 Margaret Dayhoff and her team at the National Biomedical Research Foundation (NBRF) published "The Atlas of Protein Sequence and Structure". They put all know protein sequences in the Atlas, even unpublished material. This can be seen as the first attempt to create a molecular database. They made use of the newly computerized (1964) Medical Literature Analysis and Retrieval System (MEDLARS) at the National Institutes of Health (NIH). The team used computers to store the data but had to manually type and proofread each sequence, which had a high cost in time and money. Present day We now have many sequence databases, tools for using them and easy access to them. One of the largest being GenBank which contains over 2 billion sequences. Timeline == Current issues ==

Storage & redundancy Records in sequence databases are deposited from a wide range of sources, from individual researchers to large genome sequencing centers. As a result, the sequences themselves, and especially the biological annotations attached to these sequences, may vary in quality. There is much redundancy, as multiple labs may submit numerous sequences that are identical, or nearly identical, to others in the databases. Many sequence annotations are based not on laboratory experiments, but on the results of sequence similarity searches for previously annotated sequences. Once a sequence has been annotated based on similarity to others, and itself deposited in the database, it can also become the basis for future annotations. This can lead to a transitive annotation problem because there may be several such annotation transfers by sequence similarity between a particular database record and actual wet lab experimental information. Therefore, care must be taken when interpreting the annotation data from sequence databases. Scoring methods Most of the current database search algorithms rank alignment by a score, which is usually a particular scoring system. The solution towards solving this issue is found by making a variety of scoring systems available to suit to the specific problem. Alignment statistics Searching algorithm often produce an ordered list lacking biological significance. ==See also==