Improved BLAST searches using longer words for protein seeding | Zendy

Sergey Shiryev | Zendy; Jason S. Papadopoulos | Zendy; Alejandro A. Schäffer | Zendy; Richa Agarwala | Zendy

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Improved BLAST searches using longer words for protein seeding

Author(s) -

Sergey Shiryev,

Jason S. Papadopoulos,

Alejandro A. Schäffer,

Richa Agarwala

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/btm479

Subject(s) - executable , computer science , file transfer protocol , heuristic , word (group theory) , code (set theory) , operator (biology) , data mining , artificial intelligence , information retrieval , programming language , operating system , mathematics , biology , set (abstract data type) , geometry , the internet , biochemistry , repressor , transcription factor , gene

The blastp and tblastn modules of BLAST are widely used methods for searching protein queries against protein and nucleotide databases, respectively. One heuristic used in BLAST is to consider only database sequences that contain a high-scoring match of length at most 5 to the query. We implemented the capability to use words of length 6 or 7. We demonstrate an improved trade-off between running time and retrieval accuracy, controlled by the score threshold used for short word matches. For example, the running time can be reduced by 20-30% while achieving ROC (receiver operator characteristic) scores similar to those obtained with current default parameters.

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