High Performance Computational Methods for Biological Sequence
Analysis presents biological sequence analysis using an
interdisciplinary approach that integrates biological, mathematical and
computational concepts. These concepts are presented so that computer
scientists and biomedical scientists can obtain the necessary background
for developing better algorithms and applying parallel computational
methods. This book will enable both groups to develop the depth of
knowledge needed to work in this interdisciplinary field.
This work focuses on high performance computational approaches that are
used to perform computationally intensive biological sequence analysis
tasks: pairwise sequence comparison, multiple sequence alignment, and
sequence similarity searching in large databases. These computational
methods are becoming increasingly important to the molecular biology
community allowing researchers to explore the increasingly large amounts
of sequence data generated by the Human Genome Project and other related
biological projects. The approaches presented by the authors are
state-of-the-art and show how to reduce analysis times significantly,
sometimes from days to minutes.
High Performance Computational Methods for Biological Sequence
Analysis is tremendously important to biomedical science students and
researchers who are interested in applying sequence analyses to their
studies, and to computational science students and researchers who are
interested in applying new computational approaches to biological
sequence analyses.
