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Part of the book series: Methods in Molecular Biology ((MIMB,volume 25))

Abstract

Profile analysis uses information from a group of aligned sequences to create a generalized probe, the profile, for sequence or structural motifs. The profile contains information about the location and type of sequence conservation observed in the aligned sequences, the strength of the sequence conservation, and the observed positions of gaps needed to align the sequences, and is most easily understood as a description of the envelope of sequences capable of forming a given motif. When the sequences are aligned based on their three-dimensional structure, the resulting profile describes the sequences capable of folding into such a structure, and is thus a description of the sequence properties of a structural motif. Standard methods of sequence comparison, such as alignment or database searching, can be performed using a profile instead of a single sequence, and can be thought of as the comparison of the consensus of the motif to a sequence or to a database.

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References

  1. Gribskov, M., Luthy, R., and Eisenberg, D. (1990) Profile analysis. Meth Enzym. 183, 146–159

    Article  PubMed  CAS  Google Scholar 

  2. Gribskov, M. and Burgess, R. R (1986) Sigma factors from E. coli, B. subtilis, phage SPOl, and phage T4 are homologous proteins. Nucleic Acids Res. 14, 6745–6763.

    Article  PubMed  CAS  Google Scholar 

  3. Schwartz, R. M and Dayhoff, M. O. (1979) Matrices for detecting distant relationships, in Atlas of Protein Sequence and Structure, vol. 5, Supp. 3 (Dayhoff, M O, ed), National Biomedical Research Foundation, Washington, DC, pp. 353–358

    Google Scholar 

  4. Felsenstein, J. (1973) Maximum-likelihood estimation of evolutionary trees from continuous characters. Am J. Hum. Genet. 25, 471–492.

    PubMed  CAS  Google Scholar 

  5. Altschul, S P., Carrol, R J., and Lipman, D (1989) Weights for data related by a tree. J. Mol Biol 207, 647–653.

    Article  PubMed  CAS  Google Scholar 

  6. Sibbald, P. R and Argos, P. (1989) Weighting aligned protein or nucleic acid sequences to correct for unequal representation J Mol Biol 16, 813–818.

    Google Scholar 

  7. Smith, T. F. and Waterman, M. S. (1981) Comparison of biosequences. Adv. Appl Math. 2, 482–489.

    Article  Google Scholar 

  8. Gribskov, M., Homyak, M., Edenfield, J, and Eisenberg, D (1988) Profile scanning for three-dimensional structural patterns in protein sequences CABIOS 4, 61–66.

    PubMed  CAS  Google Scholar 

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© 1994 Humana Press Inc, Totowa, NJ

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Gribskov, M. (1994). Profile Analysis. In: Computer Analysis of Sequence Data. Methods in Molecular Biology, vol 25. Springer, Totowa, NJ. https://doi.org/10.1385/0-89603-276-0:247

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  • DOI: https://doi.org/10.1385/0-89603-276-0:247

  • Publisher Name: Springer, Totowa, NJ

  • Print ISBN: 978-0-89603-276-7

  • Online ISBN: 978-1-59259-512-9

  • eBook Packages: Springer Protocols

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