Highly accurate classification of Watson-Crick basepairs on termini of single DNA molecules

Biophysical Journal

Volumn 84, Issue 2 I, 2003, Pages 967-976

  Winters Hilt, Stephen ^a,b,c   Vercoutere, Wenonah ^b   DeGuzman, Veronica S ^a,b   Deamer, David ^b   Akeson, Mark ^a,b   Haussler, David ^a,b  

^a University of California Santa Cruz   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

^c NONE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DNA;

ARTICLE; BASE PAIRING; BIOPHYSICS; CALIBRATION; DNA SEQUENCE; ION CURRENT; MATHEMATICAL ANALYSIS; MATHEMATICAL MODEL; MOLECULAR MODEL; PROBABILITY; PROTEIN FOLDING; SIGNAL PROCESSING; SIGNAL TRANSDUCTION; STRUCTURE ANALYSIS;

EID: 0037306228     PISSN: 00063495     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0006-3495(03)74913-3     Document Type: Article

References (29)

1. Akeson, M., D. Branton, J. J. Kasianowicz, E. Brandin, and D. W. Deamer. 1999. Microsecond time-scale discrimination among polycytidylic acid, polyadenylic acid, and polyuridylic acid as homopolymers or as segments within single RNA molecules. Biophys. J. 77:3227-3233.
2. Bayley, H. 2000. Pore planning: functional membrane proteins by design. J. Gen. Physiol. 116:1a.
3. Bredensteiner, E. J., and K. P. Bennett. 1999. Multicategory classification by support vector machines. Computational Optimization and Applications. 12:53-79.
4. Burges, C. J. C. 1998. A tutorial on support vector machines for pattern recognition. Data Min. Knowl. Discov. 2:121-167.
5. Chung, S. H., J. B. Moore, L. Xia, L. S. Premkumar, and P. W. Gage. 1990. Characterization of single channel currents using digital signal processing techniques based on Hidden Markov models. Philos. Trans. R. Soc. Lond. B Biol. Sci. 329:265-285.
6. Chung, S.-H., and P. W. Gage. 1998. Signal processing techniques for channel current analysis based on hidden Markov models. In Methods in Enzymology; Ion Channels, Part B. P. M. Conn, editor. Academic Press, San Diego, California. 420-437.
7. Colquhoun, D., and F. J. Sigworth. 1995. Fitting and statistical analysis of single-channel products. In Single-Channel Recording, 2nd ed. B. Sakmann and E. Neher, editors. Plenum Publishing, New York. 483-587.
8. Cormen, T. H., C. E. Leiserson, and R. L. Rivest. 1989. Introduction to Algorithms. MIT Press, Cambridge, Massachusetts.
9. Cover, T. M., and J. A. Thomas. 1991. Elements of Information Theory. Wiley-Interscience, New York.
10. Diserbo, M., P. Masson, P. Gourmelon, and R. Caterini. 2000. Utility of the wavelet transform to analyze the stationarity of single ionic channel recordings. J. Neurosci. Methods. 99:137-141.
11. Durbin, R. 1998. Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids. Cambridge University Press, Cambridge, England, and New York.
12. Freund, Y., R. Schapire, and N. Abe. 1999. A short introduction to boosting. J. Jpn. Soc. Artif. Intell. 14:771-780.
13. Gouaux, J. E., O. Braha, M. R. Hobaugh, L. Song, S. Cheley, C. Shustak, and H. Bayley. 1994. Subunit stoichiometry of staphylococcal alpha-hemolysin in crystals and on membranes: a heptameric transmembrane pore. Proc. Natl. Acad. Sci. USA. 91:12828-12831.
14. Jaakkola, T. S., and D. Haussler. 1999. Exploiting generative models in discriminative classifiers. In Advances in Neural Processing Systems 11. MIT Press, Cambridge, Massachusetts.
15. Jelinek, F. 1997. Statistical methods for speech recognition. MIT Press, Cambridge, Massachusetts.
16. Joachims, T. 1998. Chapter 11: making large-scale SVM learning practical. In Advances in Kernel Methods - Support Vector Learning. B. Scholkopf, C. J. C. Burges, and A. J. Smola, editors. MIT Press, Cambridge, Massachusetts.
17. Kasianowicz, J. J., E. Brandin, D. Branton, and D. W. Deamer. 1996. Characterization of individual polynucleotide molecules using a membrane channel. Proc. Natl. Acad. Sci. USA. 93:13770-13773.
18. Krogh, A., I. S. Mian, and D. Haussler. 1994. A hidden Markov model that finds genes in E. coli DNA. Nucleic Acids Res. 22:4768-4778.
19. Li, J., C. McMullan, D. Stein, D. Branton, and J. Golovckenko. 2001. Solid state nanopores for single molecule detection. Biophys. J. 80:339a.
20. Meller, A., L. Nivon, E. Brandin, J. Golovchenko, and D. Branton. 2000. Rapid nanopore discrimination between single polynucleotide molecules. Proc. Natl. Acad. Sci. USA. 97:1079-1084.
21. Meller, A., L. Nivon, and D. Branton. 2001. Voltage-driven DNA translocations through a nanopore. Phys. Rev. Lett. 86:3435-3438.
22. Nievergelt, Y. 1999. Wavelets Made Easy. Birkhauser, Boston, Massachusetts.
23. Osuna, E., R. Freund, and F. Girosi. 1997, An improved training algorithm for support vector machines. In Neural Networks for Signal Processing VII. J. Principe, L. Gile, N. Morgan, and E. Wilson, editors. IEEE, New York. 276-285.
24. Platt, J. C. 1998. Chapter 12: fast training of support vector machines using sequential minimal optimization. In Advances in Kernel Method-s - Support Vector Learning. B. Scholkopf, C. J. C. Burges, and A. J. Smola, editors. MIT Press, Cambridge, Massachusetts. Ch. 12.
25. SantaLucia, J. 1998. A unified view of polymer, dumbbell, and oligonucleotide DNA nearest-neighbor thermodynamics. Proc. Natl. Acad. Sci. USA. 95:1460-1465.
26. Song, L., M. R. Hobaugh, C. Shustak, S. Cheley, H. Bayley, and J. E. Gouaux. 1996. Structure of staphylococcal alpha-hemolysin, a heptameric transmembrane pore. Science. 274:1859-1866.
27. Stormo, G. D. 2000. Gene-finding approaches for eukaryotes. Genome Res. 10:394-397.
28. Vapnik, V. N. 1999. The Nature of Statistical Learning Theory, 2nd ed. Springer-Verlag, New York.
29. Vercoutere, W., S. Winters-Hilt, H. Olsen, D. W. Deamer, D. Haussler, and M. Akeson. 2001. Rapid discrimination among individual DNA hairpin molecules at single-nucleotide resolution using an ion channel. Nat. Biotechnol. 19:248-252.