Speeding up tandem mass spectrometry database search: metric embeddings and fast near neighbor search | Zendy

Debojyoti Dutta | Zendy; Ting Chen | Zendy

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Speeding up tandem mass spectrometry database search: metric embeddings and fast near neighbor search

Author(s) -

Debojyoti Dutta,

Ting Chen

Publication year - 2007

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btl645

Subject(s) - locality sensitive hashing , hash function , rolling hash , computer science , k independent hashing , hash table , database search engine , set (abstract data type) , data mining , double hashing , algorithm , database , search engine , information retrieval , computer security , programming language

Due to the recent advances in technology of mass spectrometry, there has been an exponential increase in the amount of data being generated in the past few years. Database searches have not been able to keep with this data explosion. Thus, speeding up the data searches becomes increasingly important in mass-spectrometry-based applications. Traditional database search methods use one-against-all comparisons of a query spectrum against a very large number of peptides generated from in silico digestion of protein sequences in a database, to filter potential candidates from this database followed by a detailed scoring and ranking of those filtered candidates.

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