Combined dynamic arrays for storing and searching semi-ordered tandem mass spectrometry data.
When performing bioinformatics analysis on tandem mass spectrometry data, there is a computational need to efficiently store and sort these semi-ordered datasets. To solve this problem, a new data structure based on dynamic arrays was designed and implemented in an algorithm that parses semi-ordered data made by Mascot, a separate software program that matches peptide tandem mass spectra to protein sequences in a database. By accommodating the special features of these large datasets, the combined dynamic array (CDA) provides efficient searching and insertion operations. The operations on real datasets using this new data structure are hundreds times faster than operations using binary tree and red-black tree structures. The difference becomes more significant when the dataset size grows. This data structure may be useful for improving the speed of other related types of protein assembling software or other types of software that operate on datasets with similar semi-ordered features.
Feng
Jian
J
Department of Applied Mathematics and Statistics, The Johns Hopkins University, Baltimore, Maryland, USA.
Naiman
Daniel Q
DQ
Cooper
Bret
B
D000465:Algorithms; D000595:Amino Acid Sequence; D019295:Computational Biology; D008969:Molecular Sequence Data; D020539:Sequence Analysis, Protein; D012984:Software; D013223:Statistics as Topic / Q000379:methods*; D053719:Tandem Mass Spectrometry