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Pattern Discovery in Biomolecular DataTools, Techniques, and Applications$
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Jason T. L. Wang, Bruce A. Shapiro, and Dennis Shasha

Print publication date: 1999

Print ISBN-13: 9780195119404

Published to Oxford Scholarship Online: November 2020

DOI: 10.1093/oso/9780195119404.001.0001

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PRINTED FROM OXFORD SCHOLARSHIP ONLINE (oxford.universitypressscholarship.com). (c) Copyright Oxford University Press, 2021. All Rights Reserved. An individual user may print out a PDF of a single chapter of a monograph in OSO for personal use. date: 27 September 2021

Overview: A System for Tracking and Managing the Results from Sequence Comparison Programs

Overview: A System for Tracking and Managing the Results from Sequence Comparison Programs

Chapter:
(p.160) Chapter 10 Overview: A System for Tracking and Managing the Results from Sequence Comparison Programs
Source:
Pattern Discovery in Biomolecular Data
Author(s):

David P. Yee

Tim Hunkapiller

Publisher:
Oxford University Press
DOI:10.1093/oso/9780195119404.003.0017

The Human Genome Project was launched in the early 1990s to map, sequence, and study the function of genomes derived from humans and a number of model organisms such as mouse, rat, fruit fly, worm, yeast, and Escherichia coli. This ambitious project was made possible by advances in high-speed DNA sequencing technology (Hunkapiller et al., 1991). To date, the Human Genome Project and other large-scale sequencing projects have been enormously successful. The complete genomes of several microbes (such as Hemophilus influenzae Rd, Mycoplasma genitalium, and Methanococcus jannaschii) have been completely sequenced. The genome of bacteriophage T4 is complete, and the 4.6-megabase sequence of E. coli and the 13-megabase genome of Saccharomyces cerevisiae have just recently also been completed. There are 71 megabases of the nematode Caenorhabditis elegans available. Six megabases of mouse and 60 megabases of human genomic sequence have been finished, which represent 0.2% and 2% of their respective genomes. Finally, more than 1 million expressed sequence tags derived from human and mouse complementary DNA expression libraries are publicly available. These public data, in addition to private and proprietary DNA sequence databases, represent an enormous information-processing challenge and data-mining opportunity. The need for common interfaces and query languages to access heterogeneous sequence databases is well documented, and several good systems are well underway to provide those interfaces (Woodsmall and Benson, 1993; Marr, 1996). Our own work on database and program interoperability in this domain and in computational chemistry (Gushing, 1995) has shown, however, that providing the interface is but the first step toward making these databases fully useful to the researcher. (Here, the term “database” means a collection of data in electronic form, which may not necessarily be physically deposited in a database management system [DBMS]. A scientist’s database could thus be a collection of flat files, where the term “database” means “data stored in a DBMS” is clear from the context.) Deciphering the genomes of sequenced organisms falls into the realm of analysis; there is now plenty of sequence data. The most common form of sequence analysis involves the identification of homologous relationships among similar sequences.

Keywords:   Alignment, Bioinformatics, Chromosome, Data mining, Exon, Fasta, GenBank, Homolog, Information model, Molecular biology

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