Their policies may differ from this site. This course examines the theory and methods behind sequence operations, such as genome assembly, transcriptome. Probablistic models are becoming increasingly important in analyzing the huge amount of data being produced by large-scale DNA-sequencing efforts such as the Human Genome Project. Some links on this page may take you to non-federal websites. Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids.
High-throughput techniques for DNA sequencing have led to an exponential growth of. Biological sequences generally refer to sequences of.
Some full text articles may not yet be available without a charge during the embargo (administrative interval). Biological Sequence Data Mining Trends and Research Frontiers. When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher. This book provides the first unified, up-to-date and self-. This chapter is an attempt to highlight some of the commonly used algorithms for the biological sequence analysis ranging from pairwise sequence analysis. PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH Probabilistic methods are assuming greater significance in the analysis of nucleotide sequence data. Moreover, the complete genome sequence of Penicillium expansum provided new insights into secondary metabolism biosynthetic gene clusters in fungi, especially. The resulting algorithms will be carefully tested using both real data with published benchmarks and simulated data with known optimal alignments. The proposal is to develop a robust and integrated suite of open-source tools to do both local and multiple alignments using a computer science technique that is novel in this arena and that yields exact algorithms guaranteed to find optimal solutions. The program will focus on two of the most daunting issues in aligning gene sequences: very specifically aligning small areas of protein sequences and less specifically but very defensibly aligning many sequences together. Primary Place of Performance Congressional District:Ĥ90100 NSF RESEARCH & RELATED ACTIVIT 490100 NSF RESEARCH & RELATED ACTIVIT 490100 NSF RESEARCH & RELATED ACTIVIT 490100 NSF RESEARCH & RELATED ACTIVITĪ grant has been awarded to the University of Arizona to develop a computer program to use a new and novel way of aligning protein sequences, especially those of whole genomes. The respective chapters provide detailed information on biological databases, sequence alignment, molecular evolution, next-generation sequencing, systems. John Kececioglu (Principal Investigator) Sponsored Research Office:.
Robust Tools for Biological Sequence Analysis NSF Org: