Part of the Undergraduate Texts in Mathematics book series (UTM)


In Chapter 8, we learned that DNAholds the information on how to construct a living organism and make it work. This is achieved by instructing the cell how to make proteins characteristic for that organism, one cell at a time. So biologists became interested in determining the precise sequence of the nucleotides in the DNA.

At first, this was hard to do and took a great deal of time even for small segments. Simple strands ofDNAwere the first to be attempted, those of viruses and the plasmids of bacteria. In time, new techniques were invented and sequencing became faster. A big step was made with the invention of PCR, polymerase chain reaction, for making millions of copies of a strand of DNA. Still, sequencing the genome of an organism, its entire complement of DNA, was beyond reach, except possibly that of a virus. And so it was a wildly ambitious plan when, in 1990, the U.S. government launched the Human Genome Project (HGP). The project was to sequence the entire human genome of 3 billion base pairs to an accuracy of one error in 10,000 bases.1 The science of genomics was born, and with it, biology is forever changed.


Spinal Muscular Atrophy Congenital Adrenal Hyperplasia Human Genome Project Average Mutation Rate PAM1 Matrix 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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References and Suggested Further Reading

  1. [1]
    P. Benfey and A. Protopapas, Genomics, Prentice–Hall, Englewood Cliffs, NJ, 2004.Google Scholar
  2. [2]
    D. T. Jones, W. R. Taylor, and J. M. Thornton, The rapid generation of mutation data matrices from protein sequences, Comput. Appl. Biosci., 8–3 (1992), 275282.Google Scholar
  3. [3]
    I. Korf, M. Yandell, and J. Bedell, Blast, O'Reilly, Cambridge, UK, 2003.Google Scholar
  4. [4]
    S. B. Needleman and C. D. Wunsch, A general method applicable to the search for similarities in the amino acid sequence of two proteins, J. Molecular Biol., 48-3 (1970), 443453.CrossRefGoogle Scholar
  5. [5]
    G. Smith, Genomics Age, AMACOM, New York, 2005.Google Scholar
  6. [6]
    T. F. Smith and M. S. Waterman, Identification of common molecular subsequences, J. Molecular Biol., 147–1 (1981), 195197.CrossRefGoogle Scholar
  7. [7]
    E. Ukkonen, Algorithms for string matching, Inform. Control, 64 (1985), 100118.MATHCrossRefMathSciNetGoogle Scholar

Copyright information

© Springer-Verlag New York 2009

Authors and Affiliations

  1. 1.School of MathematicsGeorgia Institute of TechnologyAtlantaUSA

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