Novel Approaches to Biomolecular Sequence Indexing

In many biomolecular database applications involving string/sequence data, it is common to have similarity search in the form of near neighbor queries or nearest neighbor queries. The similarity between strings/sequences are typically measured in terms of the least costly set of allowed edit operations that transform one string/sequence to another. In this survey, we briefly describe some of the recent developments in biomolecular sequence indexing methods that allow efficient similarity search. Our focus here is on global similarity measures that compare sequences in full; such measures are important for comparing protein sequences and smaller biomolecules. Examples include character and block edit distances and their weighted variants. Two major approaches are summarized here: distance based indexing and embeddings of general sequence similarity measures to Hamming distance, for which efficient indexing methods are available.