Applied Algorithms for Bioinformatics Problems

With significant growth of bio-molecular sequence data in the last decade the need for algorithms to extract patterns and meaningful information from such data has been felt strongly. Alignment of sequences, in order to determine regions of common descent, has also been an important area of research as it helps scientist discover the evolution of species. Another problem that researchers are putting in a lot of effort into, is document summary. As the lower bound for computation is being met for various algorithms, to further expedite the computing on large data sets, parallelization has become imperative. New multiprocessor architectures like the Cell Broadband Engine have the potential to do extensive calculations and act as mini-supercomputers. Other applications for these include onboard aircraft fault diagnosis and prognosis. We take a peek into some existing algorithms for these problems as well as propose novel algorithms along with their implementations to address these problems in the field of bioinformatics.

Autorentext

Dr. Vishal Thapar is a Post Doctoral Scientist at Cold Spring Harbor Lab, NY. He got his Ph.D. from University of Connecticut (2008) in Applied Algorithms. Since then he has been working at finding new algorithms for bioinformatics problems. This book is a collection of latest algorithms developed to solve some of these problems.