We are amidst an ongoing flood of sequence data arising from the application of high-
throughput technologies, and a concomitant fundamental revision in our understanding of …

A detailed overview of current research in kernel methods and their application to
computational biology. Modern machine learning techniques are proving to be extremely …

Large-scale genomics demands computational methods that scale sublinearly with the
growth of data. We review several data structures and sketching techniques that have been …

Although there are many advanced and specialized texts and handbooks on algorithms,
until now there was no book that focused exclusively on the wide variety of data structures …

This algorithm can be extended in various ways to provide linear time prediction cost in the
length of the sequence to be classified. We demonstrate extensions in the case of position …

We show that suffix trees store various kinds of redundant information. We exploit these
redundancies to obtain more space efficient representations. The most space efficient of our …

Most of existing text clustering algorithms use the vector space model, which treats
documents as bags of words. Thus, word sequences in the documents are ignored, while …

In this paper, we propose a phrase-based document similarity to compute the pair-wise
similarities of documents based on the suffix tree document (STD) model. By mapping each …

The enormous complexity of biological systems at the molecular level must be answered
with powerful computational methods. Computational biology is a young field, but has seen …

This book is a graduate-level textbook on data structures. A data structure is a method1 to
realize a set of operations on some data. The classical example is to keep track of a set of …