Algorithms on strings, trees, and sequences: computer science and computational biology
Algorithms on strings, trees, and sequences: computer science and computational biology
A Space-Economical Suffix Tree Construction Algorithm
Journal of the ACM (JACM)
On the sorting-complexity of suffix tree construction
Journal of the ACM (JACM)
Database System Implementation
Database System Implementation
A Database Index to Large Biological Sequences
Proceedings of the 27th International Conference on Very Large Data Bases
Practical methods for constructing suffix trees
The VLDB Journal — The International Journal on Very Large Data Bases
Genome-scale disk-based suffix tree indexing
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Practical suffix tree construction
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
A new method for indexing genomes using on-disk suffix trees
Proceedings of the 17th ACM conference on Information and knowledge management
ERA: efficient serial and parallel suffix tree construction for very long strings
Proceedings of the VLDB Endowment
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A suffix tree is a fundamental data structure for string searching algorithms. Unfortunately, when it comes to the use of suffix trees in real-life applications, the current methods for constructing suffix trees do not scale for large inputs. All the existing practical algorithms perform random access to the input string, thus requiring that the input be small enough to be kept in main memory. We are the first to present an algorithm which is able to construct suffix trees for input sequences significantly larger than the size of the available main memory. As a proof of concept, we show that our method allows to build the suffix tree for 12GB of real DNA sequences in 26 hours on a single machine with 2GB of RAM. This input is four times the size of the Human Genome, and the construction of suffix trees for inputs of such magnitude was never reported before.