Base Information Content in Organic Formulas

Journal of Chemical Information and Computer Sciences

Volumn 40, Issue 4, 2000, Pages 942-946

  Graham, Daniel J ^a   Schacht, David V ^a,b  

^a LOYOLA UNIVERSITY CHICAGO   (United States)

^b NORTHWESTERN UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 0011421663     PISSN: 00952338     EISSN: None     Source Type: Journal    
DOI: 10.1021/ci990182k     Document Type: Article

References (25)

1. Brillouin, L. Science and Information Theory, 2nd ed.; Academic: New York, 1962.
2. Herdan, G. The Advance Theory of Language as Choice and Chance; Springer-Verlag: Berlin, 1966.
3. Goldie, C. M.; Pinch, R. G. E. Communication Theory; Cambridge University Press: Cambridge, 1991.
4. Morowitz, H. J. Energy Flow in Biology; Ox Bow Press: Woodbridge, CT, 1979.
5. Feynman, R. P. In Feynman Lectures on Computation; Hey, A. J. G., Allen, R. W., Eds.; Addison-Wesley: Reading, MA, 1996.
6. Lin, S. K. Molecular diversity assessment: logarithmic relations of information and species diversity and logarithmic relations of entropy and indistinguishability after rejection of Gibbs paradox of entropy. Molecules 1996, 57-67.
7. Marsh, G. P. Lectures on the English Language; Scribner, New York, 1862.
8. Shannon, C. E. Prediction and entropy of printed English. Bell Syst. Tech. J. 1951, 30, 50-64.
9. Shannon C. E.; Weaver, W. The Mathematical theory of Communication; University of Illinois Press: Urbana, IL, 1949.
10. Gordon, J. E.; Brockwell, J. C. Chemical inference 1. Formalization of the language of organic chemistry: generic structural formulas. J. Chem. Inf. Comput. Sci. 1983, 23, 117-134.
11. Gordon, J. E.; Brockwell, J. C. Chemical inference 2. Formalization of the language of organic chemistry: generic systematic nomenclature. J. Chem. Inf. Comput. Sci. 1984, 23, 81-92.
12. Johnson, M., Maggiora, G. M., Eds. Concepts and Applications of Molecular Similarity; Wiley: New York, 1990.
13. Flower, D. R. On the properties of bit string-based measures of chemical similarity. J. Chem. Inf. Comput. Sci. 1998, 38, 379-386.
14. Chemical Applications of Graph Theory; Balaban, A. T., Ed.; Academic Press: London, 1976.
15. Turner, D. B.; Tyrrell, S. M.; Willette, P. W. Rapid quantification of molecular diversity and selective database. J. Chem. Inf. Comput. Sci. 1997, 37, 18-22.
16. Agrafiotis, D. K. Stochastic algorithms for maximizing molecular diversity. J. Chem. Inf. Comput. Sci. 1997, 37, 841-851.
17. Wiswesser, W. J. Historic development of chemical notation. J. Chem. Inf. Comput. Sci. 1985, 25, 258-263.
18. Read, R. C. A new system for the designation of chemical compounds 1. Theoretical preliminaries and the coding of acyclic compounds. J. Chem. Inf. Comput. Sci. 1983, 23, 135-149.
19. Handbook of Chemistry and Physics, Weast, R. C., Ed., Chemical Rubber Co.: Cleveland, 1972.
20. Zipf, G. K. Human Behavior and the Principle of Least Effort; Addison-Wesley: Cambridge, MA, 1949.
21. Calvin, M. Chemical Evolution; Oxford University Press: Oxford, 1969.
22. See, for example: Principles of Molecular Recognition; Buckingham, A. D., Legon, A. C., Roberts, S. M., Eds.; Blackie Academic and Professional: London, 1993.
23. Bayada, D. M.; Hamersma, H.; van Geerestein, V. J. Molecular Diversity and representativity in chemical databases. J. Chem. Inf. Comput. Sci. 1999, 39, 1-10.
24. Freund, J. E. Mathematical Statistics; Prentice-Hall: Englewood Cliffs, NJ, 1962.
25. Conover, W. J. Practical Nonparametric Statistics, 3rd ed.; Wiley: New York, 1999.