Sequence data is ubiquitous and finding frequent sequences in a large database is one of the most common problems when analyzing sequence data. Unfortunately many sources of seque...
Expressed sequence tags (ESTs) have provided a first glimpse of the collection of transcribed sequences in a variety of organisms. However, a careful analysis of this sequence dat...
John Quackenbush, Feng Liang, Ingeborg Holt, Geo P...
Background: Rates of substitution in protein-coding sequences can provide important insights into evolutionary processes that are of biomedical and theoretical interest. Increased...
Estienne C. Swart, Winston A. Hide, Cathal Seoighe
We explore how recent data-mining-based tools developed in domains such as biomedicine or text-mining for extracting interesting knowledge from sequence data could be applied to pe...
Gilbert Ritschard, Alexis Gabadinho, Nicolas S. M&...
Background: Recent advances and automation in DNA sequencing technology has created a vast amount of DNA sequence data. This increasing growth of sequence data demands better and ...
A. K. M. A. Baten, Bill C. H. Chang, Saman K. Halg...
Background: Accurate identification of splice sites in DNA sequences plays a key role in the prediction of gene structure in eukaryotes. Already many computational methods have be...
A. K. M. A. Baten, Saman K. Halgamuge, Bill C. H. ...
Background: Advances in automated DNA sequencing technology have accelerated the generation of metagenomic DNA sequences, especially environmental ribosomal RNA gene (rDNA) sequen...
Supervised learning on sequence data, also known as sequence classification, has been well recognized as an important data mining task with many significant applications. Since te...
Zhengzheng Xing, Jian Pei, Guozhu Dong, Philip S. ...
Sequence data analysis has been extensively studied in the literature. However, most previous work focuses on analyzing sequence data from a single source or party. In many applica...