An error-correcting code framework for genetic sequence analysis

Journal of the Franklin Institute

Volumn 341, Issue 1-2, 2004, Pages 89-109

  May, Elebeoba E ^a   Vouk, Mladen A ^b   Bitzer, Donald L ^b   Rosnick, David I ^b  

^a SANDIA NATIONAL LABORATORIES   (United States)

^b North Carolina State University   (United States)

Author keywords

Biological coding theory; Coding theory; Error correcting codes; Information theory; Translation initiation

Indexed keywords

CELLS; CODES (SYMBOLS); DNA; ERROR CORRECTION; INFORMATION DISSEMINATION; INFORMATION THEORY;

BIOLOGICAL CODING THEORY; CODING THEORY; ERROR CORRECTING CODES; TRANSLATION INITIATION;

GENETIC ENGINEERING;

EID: 1542427271     PISSN: 00160032     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jfranklin.2003.12.009     Document Type: Conference Paper

References (79)

1. Roman-Roldan R., Bernaola-Galvan P., Oliver J.L. Application of information theory to DNA sequence analysis. a review Pattern Recognition. 29(7):1996;1187-1194.
2. Sarkar R., Roy A.B., Sarkar P.K. Topological information content of genetic molecules - I. Math. Biosci. 39:1978;299-312.
3. Fowler T.B. Computation as a thermodynamic process applied to biological systems. Int. J. Biomed. Comput. 10(6):1979;477-489.
4. Shannon C.E., Weaver W. The Mathematical Theory of Communication. 1949;University of Illinois Press, Urbana, IL.
5. K. Palaniappan, M.E. Jernigan, Pattern analysis of biological sequences, in: Proceedings of the 1984 IEEE International Conference on Systems, Man, and Cybernetics, Halifax, Canada, 10-12 October 1984.
6. Almagor H. Nucleotide distribution and the recognition of coding regions in DNA sequences. an information theory approach J. Theor. Biol. 117:1985;127-136.
7. Schneider T.D. Theory of molecular machines. II. Energy dissipation from molecular machines. J. Theor. Biol. 148:1991;125-137.
8. Schneider T.D. Theory of molecular machines. I. Channel capacity of molecular machines. J. Theor. Biol. 148:1991;83-123.
9. Altschul S.F. Amino acid substitution matrices from an information theoretic perspective. J. Mol. Biol. 219:1991;555-565.
10. Salamon P., Konopka A.K. A maximum entropy principle for the distribution of local complexity in naturally occuring nucleotide sequences. Comput. Chem. 16(2):1992;117-124.
11. Oliver J.L., Bernaola-Galvan P., Guerrero-Garcia J., Roman-Roldan R. Entropic profiles of DNA sequences through chaos-game-derived images. J. Theor. Biol. 160:1993;457-470.
12. F.M. De La vega, C. Cerpa, G. Guarneros, A mutual information analysis of tRNA sequence and modification patterns distinctive of species and phylogenetic domain, in: Pacific Symposium on Biocomputing, Hawaii, USA, 1996, pp. 710-711.
13. Schneider T.D., Mastronarde D.N. Fast multiple alignment of ungapped DNA sequences using information theory and a relaxation method. Discrete Appl. Math. 71:1996;259-268.
14. Strait B.J., Dewey T.G. The Shannon information entropy of protein sequences. Biophys. J. 71:1996;148-155.
15. Pavesi A., De Iaco B., Granero M.I., Porati A. On the informational content of overlapping genes in prokaryotic and eukaryotic viruses. J. Mol. Evol. 44(6):1997;625-631.
16. D. Loewenstern, P.N. Yianilos, Significantly lower entropy estimates for natural DNA sequences, in: Proceedings of the Data Compression Conference, Snowbird, UT, USA, 25-27 March 1997.
17. Schneider T.D. Information content of individual genetic sequences. J. Theor. Biol. 189:1997;427-441.
18. Schneider T.D. Measuring molecular information. J. Theor. Biol. 201:1999;87-92.
19. Gatlin L.L. Information Theory and the Living System. 1972;Columbia University Press, New York, NY.
20. Yockey H. Information Theory and Molecular Biology. 1992;Cambridge University Press, New York, NY.
21. Eigen M. The origin of genetic information: viruses as models. Gene. 135:1993;37-47.
22. Arques D.G., Michel C.J. A code in the protein coding genes. Biosystems. 44:1997;107-134.
23. Stambuk N. On circular coding properties of gene and protein sequences. Croat. Chem. Acta. 72(4):1999;999-1008.
24. Sengupta R., Tompa M. Quality control in manufacturing oligo arrays. a combinatorial design approach J. Comput. Biol. 9(1):2002;1-22.
25. Kari L., Kari J., Landweber L.F. Reversible molecular computation in ciliates. Karhumaki J., Maurer H., Paun G., Rozenberg G. Jewels are Forever, Contributions on Theoretical Computer Science in Honor of Arto Salomaa. 1999;353-363 Springer, Berlin.
26. MacDonaill D. A parity code interpretation of nucleotide alphabet composition. Chem. Commun. 18:2002;2062-2063.
27. Forsdyke D.R. Are introns in-series error-detecting sequences? J. Theor. Biol. 93:1981;861-866.
28. Liebovitch L.S., Tao Y., Todorov A., Levine L. Is there an error correcting code in DNA? Biophys. J. 71:1996;1539-1544.
29. E. May, M. Vouk, D. Bitzer, D. Rosnick, Analysis of coding theory based models for initiating protein translation in prokaryotic organisms, in: Fifth International Workshop on Information Processing in Cells and Tissues, Lausanne, Switzerland, September 2003.
30. G. Rosen, J. Moore, Investigation of coding structure in DNA, in: ICASSP 2003, Hong Kong, 2003.
31. Berlekamp E.R. Algebraic Coding Theory. 1968;McGraw-Hill, New York, NY.
32. Stambuk N. Symbolic cantor algorithm (SCA). a method for analysis of gene and protein coding Period. Biol. 101(4):1999;355-361.
33. D.R. Powell, D.L. Dowe, L. Allison L, T.I. Dix, Discovering simple DNA sequences by compression, in: Pacific Symposium on Biocomputing, Hawaii, USA, 1998, pp. 597-608.
34. Cover T.M., Thomas J.A. Elements of Information Theory. 1991;Wiley, New York, NY.
35. D.M. Loewenstern, H.M. Berman, H. Hirsh, Maximum a posteriori classification of DNA structure from sequence information, in: Pacific Symposium on Biocomputing, Hawaii, USA, 1998, pp. 669-680.
36. Loewenstern D., Yianilos P.N. Significantly lower entropy estimates for natural DNA sequences. J. Comput. Biol. 6(1):1999;125-142.
37. O. Delgrange, M. Dauchet, E. Rivals, Location of repetitive regions in sequences by optimizing a compression method, in: Pacific Symposium on Biocomputing, Hawaii, USA, 1999, pp. 254-265.
38. Maley C.C. DNA computation. theory, practice, and prospects Evol. Comput. 6(3):1998;201-229.
39. Adleman L., Rothemund P., Roweis S., Winfree E. On applying molecular computation to the data encryption standard. J. Comput. Biol. 6(1):1999;53-63.
40. Landweber L.F., Kari L. The evolution of cellular computing. nature's solution to a computational problem Biosystems. 52:1999;3-13.
41. Boneh D., Dunworth C., Lipton R.J., Sgall J. Making DNA computers error resistant. Landweber L., Baum E. DNA Based Computers II, DIMACS: Series in Discrete Mathematics and Theoretical Computer Science. Vol. 44:1999;165-172 American Mathematical Society, DIMACS, Providence, RI.
42. D.H. Wood, Applying error correcting codes to DNA computing, in: Fourth DIMACS Workshop on DNA Based Computers, Philadelphia, PA, USA, June 1998.
43. Hayes B. The invention of the genetic code. Am. Sci. 86(1):1998;8-14.
44. S.W. Golomb, Efficient coding for the desoxyribonucleic channel, Proceedings of the Symposia in Applied Mathematics, New York, NY, USA, Mathematical Problems in the Biological Sciences, Vol. 14, American Mathematical Society, Providence, RI, 5-8 April 1961, pp. 87-100.
45. Konopka A.K. Theory of degenerate coding and informational parameters of protein coding genes. Biochimie. 67:1985;455-468.
46. J. Reif, T. LaBean, Computationally inspired biotechnologies: improved DNA synthesis and associative search using error-correcting codes and vector-quantization, in: A. Condon (Ed.), DNA Computing: Sixth International Meeting on DNA-Based Computers (DNA6), DIMACS Series in Discrete Mathematics and Theoretical Computer Science, Leiden, The Netherlands, June 2000.
47. Sweeney P. Error Control Coding an Introduction. 1991;Prentice-Hall, New York, NY.
48. Dholakia A. Introduction to Convolutional Codes with Applications. 1994;Kluwer Academic Publishers, Norwell, MA.
49. Lin Shu, Costello D.J. Jr. Error Control Coding: Fundamentals and Applications. 1983;Prentice-Hall, Englewood Cliffs, NJ.
50. Battail G. Does information theory explain biological evolution? Europhys. Lett. 40(3):1997;343-348.
51. Dawkins R. The Selfish Gene. 1976;Oxford University Press, Oxford.
52. Dawkins R. The Blind Watchmaker. 1986;Longman, New York.
53. Anderson J.B., Mohan S. Source and Channel Coding An Algorithmic Approach. 1991;Kluwer Academic Publishers, Boston, MA.
54. Blahut R.E. Theory and Practice of Error Control Codes. 1983;Addison-Wesley, Reading, MA.
55. Lewin B. Genes V. 1995;Oxford University Press, New York, NY.
56. E.E. May, Analysis of coding theory based models for initiating protein translation in prokaryotic organisms, Ph.D. Thesis, North Carolina State University, Raleigh, NC, March 2002.
57. Watson J., Hopkins N., Roberts J., Steitz J., Weiner A. Molecular Biology of the Gene. 1987;The Benjamin Cummings Publishing Company, Inc. Menlo Park, CA.
58. E.E. May, Comparative analysis of information based models for initiating protein translation in Escherichia coli K-12, M.S. Thesis, NCSU, December 1998.
59. Szathmary E. The origin of the genetic code: amino acids as cofactors in an RNA world. Trends Genet. 16(1):2000;17-19.
60. Knight R.D., Landweber L.F. Guilt by association. the arginine case revisited RNA. 6(4):2000;499-510.
61. Gold L., Stormo G. Translational initiation. Neidhandt F., Ingraham J., Low K., Magasanik B., Schaechter M., Umbarger H. Escherichia coli and Salmonella typhimurium: Cellular and Molecular Biology. 1987;1302-1307 ASM Press, Washington, DC, USA.
62. D.E. Draper, Translation initiation, in: F.C. Neidhardt (Ed.), Escherichia coli and Salmonella, Cellular and Molecular Biology, American Society for Microbiology, Washington, DC, USA, September 1999.
63. Schneider T.D., Stormo G.D., Gold L., Dhrenfeucht A. Information content of binding sites on nucleotide sequences. J. Mol. Biol. 188:1986;415-431.
64. E.E. May, M.A. Vouk, D.L. Bitzer, D.I. Rosnick, Coding model for translation in E. coli K-12, in: First Joint Conference of EMBS-BMES, Atlanta, GA, USA, 1999.
65. E.E. May, M.A. Vouk, D.L. Bitzer, D.I. Rosnick, The ribosome as a table-driven convolutional decoder for the Escherichia coli K-12 translation initiation system, in: World Congress on Medical Physics and Biomedical Engineering Conference, Chicago, IL, USA, 2000.
66. Frishman D., Mironov A., Gelfand M. Starts of bacterial genes. estimating the reliability of computer predictions Gene. 234(2):1999;257-265.
67. M. Tompa, An exact method for finding short motifs in sequences, with application to the ribosome binding site problem, in: ISMB, Heidelberg, Germany, 1999.
68. Hannenhalli S.S., Hayes W.S., Hatzigeorgiou A.G., Fickett J.W. Bacterial start site prediction. Nucleic Acids Res. 27(17):1999;3577-3582.
69. Walker M.M., Pavlovic V., Kasif S. A comparative genomic method for computational identification of prokaryotic translation initiation sites. Nucleic Acids Res. 30(14):2002;3181-3191.
70. Zien A., Ratsch G., Mika S., Scholkopf B., Lengauer T., Muller K.R. Engineering support vector machine kernels that recognize translation initiation sites. Bioinformatics. 16(9):2000;799-807.
71. Suzek B.E., Ermolaeva M.D., Schreiber M., Salzberg S.L. A probabilistic method for identifying start codons in bacterial genomes. Bioinformatics. 17(12):2001;1123-1130.
72. Yada T., Totoki Y., Takagi T., Nakai K. A novel bacterial gene-finding system with improved accuracy in locating start codons. DNA Res. 8(3):2001;97-106.
73. Besemer J., Lomsadze A., Borodovsky M. GeneMarkS. a self-training method for prediction of gene starts in microbial genomes. Implications for finding sequence motifs in regulatory regions Nucleic Acids Res. 29(12):2001;2607-2618.
74. A.G. Pedersen, H. Nielsen, Neural network prediction of translation initiation sites in eukaryotes: perspectives for EST and genome analysis, in: Proceedings of the International Conference on Intelligent Systems and Molecular Biology, Halkidika, Greece, 21-26 June 1997, pp. 226-233.
75. Osada Y., Saito R., Tomita M. Analysis of base-pairing potentials between 16S rRNA and. 5′ UTR for translation initiation in various prokaryotes Bioinformatics. 15:1999;578-581.
76. P. Bermel, E. Eni, M. Vouk, D. Bitzer, On the Import of the Shine-Dalgarno Series to the Expression of mRNA Sequences, Department of Computer Science, North Carolina State University, NC.
77. D.L. Bitzer, M.A. Vouk, A table-driven (feedback) decoder, in: Tenth Annual International Phoenix Conference on Computers and Communications, Phoenix, AZ, USA, 1991, pp. 385-392.
78. Barnes T.M. Using Genetic Algorithms to Find the Best Generators for Half-Rate Convolutional Coding. 1994;North Carolina State University, Raleigh, NC.
79. David I. Rosnick, Free Energy Periodicity and Memory Model for E. coli Codings, Ph.D. Thesis, North Carolina State University, Raleigh, NC, 2001.