1887

Abstract

All identification processes are strictly probabilistic. Identification allocates initially unidentified operational taxonomic units (U-OTUs) to taxa contained in previously established classifications. Identification is therefore subject to a number of a priori conditions, such as the probabilistic nature of classifications, the manner in which classifications are made, the adequacy of classifications, and the adequacy of the set of characters describing U-OTUs. The advantages and disadvantages of continuous reclassification, incorporating U-OTUs, are discussed. Numerical identification is concerned with extracting from a classification a minimum, or near minimum, amount of information necessary to effect separation of all the taxa defined by the classification. Several strategies are available for achieving this-test reduction, OTU reduction, a combination of both of these, and key generation.

Loading

Article metrics loading...

/content/journal/ijsem/10.1099/00207713-24-4-494
1974-10-01
2022-01-20
Loading full text...

Full text loading...

/deliver/fulltext/ijsem/24/4/ijs-24-4-494.html?itemId=/content/journal/ijsem/10.1099/00207713-24-4-494&mimeType=html&fmt=ahah

References

  1. Gower J. C., Barnett J. A. 1971; Selecting tests in diagnostic keys with unknown responses. Nature (London) 232:491–493
    [Google Scholar]
  2. Gyllenberg H. G. 1963; A general method for deriving determination schemes for random collections of microbial isolates. Ann. Acad. Sci. Fenn. Ser. A4 69:1–23
    [Google Scholar]
  3. Gyllenberg H. G. 1965; A model for computer identification of microorganisms. J. Gen. Microbiol. 39:401–405
    [Google Scholar]
  4. Hall A. V. 1970; A computer-based system for forming identification keys. Taxon 19:12–18
    [Google Scholar]
  5. Hill L. R. 1972; Prospectives for Mycoplasma classification using multivariate analysis methods. Med. Microbiol. Immunol. 157:101–112
    [Google Scholar]
  6. Hill L. R., Silvestri L. G. 1962; Quantitative methods in the systematics of actinomycetales. III. The taxonomic significance of physiological- biochemical characters and the construction of a diagnostic key. Gen. Microbiol. 10:1–28
    [Google Scholar]
  7. Hill L. R., Silvestri L. G., Ihm P., Farchi G., Lanciani P. 1965; Automatic classification of staphylococci by principal-component analysis and a gradient method. J. Bacteriol. 89:1393–1401
    [Google Scholar]
  8. Lapage S. P. 1974; Practical aspects of probabilistic identification of bacteria. Int. J. Syst. Bacteriol. 24:500–507
    [Google Scholar]
  9. Liston J., Wiebe W., Colwell R. R. 1963; Quantitative approach to the study of bacterial species. J. Bacteriol. 85:1061–1070
    [Google Scholar]
  10. Metcalf Z. P. 1954; The construction of keys. Syst. Zool. 3:38–45
    [Google Scholar]
  11. Moller F. 1962; Quantitative methods in the systematics of actinomycetales.. IV. The theory and application of a probabilistic identification key. Gen. Microbiol. 10:29–47
    [Google Scholar]
  12. Morse L. E. 1971; Specimen identification and key construction with time-sharing computers. Taxon 20:269–282
    [Google Scholar]
  13. Niemela S. L., Gyllenberg H. G. 1968; Application of numerical methods to the identification of micro-organisms. Spisy Prirodoved. Fak. Univ. Brne 43: Series K279–289
    [Google Scholar]
  14. Niemela S., Hopkins L. J. W., Quadling C. 1968; Selecting an economical binary test battery for a set of microbial cultures. Can. J. Microbiol. 14:271–279
    [Google Scholar]
  15. Pankhurst R. J. 1970; A computer program for generating diagnostic keys. Computer J. 13:145–151
    [Google Scholar]
  16. Rescigno A., Maccacaro G. A. 1961; The information content of biological classifications. p 437–446 In Cherry C. (ed.) Information theory-a symposium held at the Royal Institution, London 1960 Butterworth; London:
    [Google Scholar]
  17. Rypka E. W., Clapper W. E., Bowen I. G., Babb R. 1967; A model for the identification of bacteria. J. Gen. Microbiol. 46:407–424
    [Google Scholar]
  18. Silvestri L. G., Hill L. R. 1964 Some problems of the taxometric approach. p 87–103 In Heywood V. H., McNeill J. (ed.) Phenetic and phylogenetic classification The Systematics Association Publication No. 6 London:
    [Google Scholar]
  19. Silvestri L. G., Turri M., Hill L. R., Gilardi E. 1962; A quantitative approach to the systematics of actinomycetes based on overall similarity. p 333–360 In Ainsworth G. C., Sneath P. H. A. (ed.) Microbial classification, 12th Symposium of the Society for General Microbiology Cambridge University Press; Cambridge:
    [Google Scholar]
  20. Tsukamura M. 1967; A statistical approach to the definition of bacterial species. Jap. J. Microbiol. 11:213–220
    [Google Scholar]
  21. Tsukamura M., Mizuno S. 1968; “Hypothetical mean organisms” of mycobacteria. A study of classification of mycobacteria. Jap. J. Microbiol. 12:371–384
    [Google Scholar]
http://instance.metastore.ingenta.com/content/journal/ijsem/10.1099/00207713-24-4-494
Loading
/content/journal/ijsem/10.1099/00207713-24-4-494
Loading

Data & Media loading...

Most cited this month Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error