Wavelets in chemistry and cheminformatics

Reviews in Computational Chemistry

Volumn 22, Issue , 2006, Pages 295-329

  Sundling, C Matthew ^a   Sukumar, Nagamani ^a   Zhang, Hongmei ^a   Embrechts, Mark J ^a   Breneman, Curt M ^a  

^a RENSSELAER POLYTECHNIC INSTITUTE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 33749988557     PISSN: 10693599     EISSN: None     Source Type: Book Series    
DOI: 10.1002/0471780367.ch5     Document Type: Review

References (163)

1. G. Bachman, L. Narici, and E. Beckenstein, Fourier and Wavelet Analysis, Springer-Verlag, New York, 2000.
2. A. Teolis, Computational Signal Processing with Wavelets, Birkhäuser, Boston, Massachusetts, 1998.
3. I. Daubechies, Ten Lectures on Wavelets, Society for Industrial and Applied Mathematics (SIAM), Philadelphia, Pennsylvania, 1992.
4. R. M. Rao and A. S. Bopardikar, Wavelet Transforms: Introduction to Theory and Applications, Addison-Wesley, Reading, Massachusetts, 1998.
5. A. Grossman and J. Morlet, SIAM J. Math. Anal., 15(4), 723-736 (1984). Decompositions of Hardy Functions into Square Integrable Wavelets of Constant Shape.
6. Y. Meyer, Wavelets: Algorithms and Applications, Society for Industrial and Applied Mathematics (SIAM), Philadelphia, Pennsylvania, 1993.
7. Y. Mallet, IEEE T. Pattern Anal., 11, 674-693 (1989). A Theory for Multiresolution Signal Decomposition - the Wavelet Representation.
8. R. R. Coifman, Y. Meyer, S. Quake and M. V. Wickerhauser, in Wavelets and Their Applications, Vol. 442, J. S. Byrnes, J. L. Byrnes, K. A. Hargreaves, and K. Berry, Eds., Kluwer Academic Publishers, Norwell, Massachusetts, 1994, pp. 363-379. Signal Processing and Compression with Wavelet Packets.
9. B. Walczak, Wavelets in Chemistry, Vol. 22, Elsevier Science, New York, 2000.
10. A. Felinger, Data Analysis and Signal Processing in Chromatography, Vol. 21, Elsevier Health Sciences, Amsterdam, the Netherlands, 1998.
11. B. K. Alsberg, A. M. Woodward, and D. B. Kell, Chemom. Intell. Lab. Syst., 37, 215-239 (1997). An Introduction to Wavelet Transforms for Chemometricians: A Time-Frequency Approach - A Tutorial.
12. U. Depczynski, K. Jetter, K. Molt, and A. Niemöller, Chemom. Intell. Lab. Syst., 39, 19-27 (1997). The Fast Wavelet Transform on Compact Intervals as a Tool in Chemometrics. I. Mathematical Background.
13. J. J. Workman, D. J. Veltkamp, S. Doherty, B. B. Anderson, K. E. Creasy, M. Koch, J. F. Tatera, A. L. Robinson, L. Bond, L. W. Burgess, G. N. Bokerman, A. H. Ullman, G. P. Darsey, F. Mozayeni, J. A. Bamberger, and M. S. Greenwood, Anal. Chem., 71, 121R-180R (1999). Process Analytical Chemistry.
14. X. Shao, A. K.-M. Leung, and F.-T. Chau, Acc. Chem. Res., 36, 276-283 (2003). Wavelet: A New Trend in Chemistry.
15. A. K.-M. Leung, F.-T. Chau, and J.-B. Gao, Chemom. Intell. Lab. Syst., 43, 165-184 (1998). A Review on Applications of Wavelet Transform Techniques in Chemical Analysis: 1989-1997.
16. S. Wold and M. Sjöström, Chemom. Intell. Lab. Syst., 44, 3-14 (1998). Chemometrics, Present and Future Success.
17. H. C. Smit and E. J. van den Heuvel, in Chemometrics and Species Identification, Vol. 141, C. Armanino, M. Forina, P. H. E. Gardiner, E. J. Van Den Heuvel, G. Kateman, S. Lanteri, H. C. Smit, and B. G. M. Vandeginste, Eds., Springer-Verlag, New York, 1987, pp. 63-89. Signal and Data Analysis in Chromatography.
18. J. Trygg, Wavelets in Chemometrics - Compression, Denoising, and Feature Extraction, 2003 Available: http://wwiv.acc.umu.se/~tnkjtg/Chemometrics/ Editorial.
19. B. B. Hubbard, The World According to Wavelets, A K Peters, Ltd., Natick, Massachusetts, 1998.
20. C. Gonnet and B. Torrésani, Signal Process., 37, 389-404 (1994). Local Frequency Analysis with the Two-Dimensional Wavelet Transform.
21. J. Blanc-Talon and D. C. Popescu, Imaging and Vision Systems: Theory, Assessment and Applications, Nova Science Publishers, Inc., Hauppauge, New York, 2001.
22. M. Misiti, Y. Misiti, G. Oppenheim, and J.-M. Poggi Wavelet Toolbox User's Guide Version 3, The MathWorks, Inc., Natick, Massachusetts, 2004.
23. B. Walczak and D. L. Massart, Chemom. Intell. Lab. Syst., 36, 81-94 (1997). Noise Suppression and Signal Compression Using the Wavelet Packet Transform - A Tutorial.
24. R. R. Coifman and M. V. Wickerhauser, IEEE T. Inform. Theory, 38(2), 713-718 (1992). Entropy-Based Algorithms for Best Basis Selection.
25. V. J. Barclay and R. F. Bonner, Anal. Chem., 69, 78-90 (1997). Application of Wavelet Transforms to Experimental Spectra: Smoothing, Denoising, and Data Set Compression.
26. C. Cai and P. d. B. Harrington, J. Chem. Inf. Comput. Sci., 38, 1161-1170 (1998). Different Discrete Wavelet Transforms Applied to Denoising Analytical Data.
27. C. R. Mittermayr, S. G. Nikolov, H. Hutter, and M. Grasserbauer, Chemom. Intell. Lab. Syst., 34, 187-202 (1996). Wavelet Denoising of Gaussian Peaks: A Comparative Study.
28. C. Perrin, B. Walczak, and D. L. Massart, Anal. Chem., 73, 4903-4917 (2001). The Use of Wavelets for Signal Denoising in Capillary Electrophoresis.
29. D. L. Donoho, in Different Perspectives on Wavelets, Vol. 47, I. Daubechies, Ed., American Mathematical Society, Providence, Rhode Island, 1993, pp. 173-205. Nonlinear Wavelet Methods for Recovery of Signals, Densities, and Spectra from Indirect and Noisy Data.
30. M. Wolkenstein, H. Hutter, and M. Grasserbauer, Fresenius J. Anal. Chem., 358, 165-169 (1997). Wavelet Filtering for Analytical Data.
31. D. L. Donoho, IEEE T. Inform. Theory, 41(3), 613-627 (1995). De-Noising by Soft-Thresholding.
32. S. Sakakibara, in Wavelets: Theory, Algorithms, and Applications, C. K. Chui, L. Montefusco, and L. Puccio, Eds., Academic Press, New York, 1994, pp. 179-196. A Practice of Data Smoothing by B-spline Wavelets.
33. B. K. Alsberg, A. M. Woodward, M. K. Winson, J. Rowland, and D. B. Kell, Analyst, 122, 645-652 (1997). Wavelet Denoising of Infrared Spectra.
34. C. R. Mittermayr, H. Frischenschlager, E. Rosenberg, and M. Grasserbauer, Fresenius J. Anal. Chem., 358, 456-464 (1997). Filtering and Integration of Chromatographic Data: A Tool to Improve Calibration?
35. X. Shao and W. Cai, J. Chemom., 12, 85-93 (1998). Resolution of Multicomponent Chromatograms by Window Factor Analysis with Wavelet Transform Preprocessing.
36. D. Jouan-Rimbaud, B. Walczak, R. J. Poppi, O. E. de Noord, and D. L. Massart, Anal. Chem., 69, 4317-4323 (1997). Application of Wavelet Transform To Extract the Relevant Component from Spectral Data for Multivariate Calibration.
37. A. M. Woodward, B. K. Alsberg, and D. B. Kell, Chemom. Intell. Lab. Syst., 40, 101-107 (1998). The Effect of Heteroscedastic Noise on the Chemometric Modelling of Frequency Domain Data.
38. H.-W. Tan and S. D. Brown, J. Chemom., 16, 228-240 (2002). Wavelet Analysis Applied to Removing Non-Constant, Varying Spectroscopic Background in Multivariate Calibration.
39. X.-Q. Lu and J.-Y. Mo, Analyst, 121, 1019-1024 (1996). Spline Wavelet Multi-Resolution Analysis for High-Noise Digital Signal Processing in Ultraviolet-Visible Spectrophotometry.
40. M. Wolkenstein, T. Stubbings, and H. Hutter, Fresenius J. Anal. Chem., 365, 63-69 (1999). Robust Automated Three-Dimensional Segmentation of Secondary Ion Mass Spectrometry Image Sets.
41. M. Wolkenstein, H. Hutter, S. G. Nikolov, and M. Grasserbauer, Fresenius J. Anal. Chem., 357, 783-788 (1997). Improvement of SIMS Image Classification by Means of Wavelet De-Noising.
42. S. G. Nikolov, H. Hutter, and M. Grasserbauer, Chemom. Intell. Lab. Syst., 34, 263-273 (1996). De-Noising of SIMS Images via Wavelet Shrinkage.
43. X.-N. Li, Y.-Z. Liang, and F.-T. Chau, Chemom. Intell. Lab. Syst., 63, 139-153 (2002). Smoothing Methods Applied to Dealing with Heteroscedastic Noise in GC/MS.
44. H. Fang and H.-Y. Chen, Anal. Chim. Acta, 346, 319-325 (1997). Wavelet Analyses of Electroanalytical Chemistry Responses and an Adaptive Wavelet Filter.
45. L. Bao, J. Mo, and Z. Tang, Anal. Chem., 69, 3053-3057 (1997). The Application in Processing Analytical Chemistry Signals of a Cardinal Spline Approach to Wavelets.
46. D. N. S. Permann and H. Teitelbaum, J. Phys. Chem., 97, 12670-12673 (1993). Wavelet Fast Fourier Transform (WFFT) Analysis of a Millivolt Signal for a Transient Oscillating Chemical Reaction.
47. B. B. Goldman and W. T. Wipke, J. Chem. Inf. Comput. Sci., 40, 644-658 (2000). Quadratic Shape Descriptors. 1. Rapid Superposition of Dissimilar Molecules Using Geometrically Invariant Surface Descriptors.
48. J. Mao, P. Sun, Z. Pan, Q. Su, and Z. Maosen, Fresenius J. Anal. Chem., 361, 140-142 (1998). Wavelet Analysis on Photoacoustic Spectra of Degraded PVC.
49. G. Beylkin, SIAM J. Numer. Anal., 29(6), 1716-1740 (1992). On the Representation of Operators in Bases of Compactly Supported Wavelets.
50. W. Dahmen and C. A. Micchelli, SIAM J. Numer. Anal., 30(2) 507-537 (1993). Using the Refinement Equation for Evaluating Integrals of Wavelets.
51. E. J. Stollnitz, T. D. Derose, and D. H. Salesin, IEEE Comput. Graph., 15(3), 76-84 (1995). Wavelets for Computer Graphics: A Primer, Part 1 - A Tutorial.
52. E. J. Stollnitz, T. D. Derose, and D. H. Salesin, IEEE Comput. Graph., 15(4), 75-85 (1995). Wavelets for Computer Graphics: A Primer, Part 2 - A Tutorial.
53. D. Marr and E. Hildreth, Proc. R. Soc. Lond. B. Bio., 207(1167), 187-217 (1980). Theory of Edge Detection.
54. J.-P. Antoine, R. Murenzi, and B. Piette, in Wavelet and Applications, Vol. 20, Y. Meyer, Ed., Masson and Springer-Verlag, Paris, 1992, pp. 144-159. Image Analysis with 2D Continuous Wavelet Transform: Detection of Position, Orientation and Visual Contrast of Simple Objects.
55. R. R. Klevecz, Funct. Integr. Genomics, 1, 186-192 (2000). Dynamic Architecture of the Yeast Cell Cycle Uncovered by Wavelet Decomposition of Expression Microarray Data.
56. P. Teppola and P. Minkkinen, J. Chemom., 14, 383-399 (2000). Wavelet-PLS Regression Models for Both Exploratory Data Analysis and Process Monitoring.
57. F. Ehrentreich, Anal. Bioanal. Chem., 372, 115-121 (2002). Wavelet Transform Applications in Analytical Chemistry.
58. X. Shao, W. Cai, P. Sun, M. Zhang, and G. Zhao, Anal. Chem., 69, 1722-1725 (1997). Quantitative Determination of the Components in Overlapping Chromatographic Peaks Using Wavelet Transform.
59. L. Sun, W. Cai, and X. Shao, Fresenius J. Anal. Chem., 370, 16-21 (2001). A Two-Dimensional Immune Algorithm for Resolution of Overlapping Two-Way Chromatograms.
60. S. Hai-Lin, W. Ji-Hong, L. Yi-Zeng, and C. Wen-Can, Chem. J. Chinese U., 18(4), 530-534 (1997). Multiresolution Analysis of Hyphenated Chromatographic Data.
61. H. Shen, J. Wang, Y. Liang, K. Pettersson, M. Josefson, J. Gottfries, and F. Lee, Chemom. Intell. Lab. Syst., 37, 261-269 (1997). Chemical Rank Estimation by Multiresolution Analysis for Two-way Data in the Presence of Background.
62. X. Shao, W. Cai, and P. Sun, Chemom. Intell. Lab. Syst., 43, 147-155 (1998). Determination of the Component Number in Overlapping Multicomponent Chromatogram Using Wavelet Transform.
63. X. Shao and S. Hou, Anal. Sci., 15, 681-684 (1999). On-Line Resolution of Overlapping Chromatograms Using the Wavelet Transform.
64. X. Zhang, J. Jin, J. Zheng, and H. Gao, Anal. Bioanal. Chem., 377(7-8), 1153-1158 (2003). Genetic Algorithms Based on Wavelet Transform for Resolving Simulated Overlapped Spectra.
65. N. Lu, F. Wang, and F. Gao, Ind. Eng. Chem. Res., 42, 4198-4207 (2003). Combination Method of Principal Component and Wavelet Analysis for Multivariate Process Monitoring and Fault Diagnosis.
66. C. L. Stork, D. J. Veltkamp, and B. R. Kowalski, Appl. Spectrosc., 52(10), 1348-1352 (1998). Detecting and Identifying Spectral Anomalies Using Wavelet Processing.
67. L. Nie, S. Wu, X. Lin, L. Zheng, and L. Rui J. Chem. Inf. Comput. Sci., 42, 274-283 (2002). Approximate Derivative Calculated by Using Continuous Wavelet Transform.
68. J. Chen and X. Z. Wang J. Chem. Inf. Comput. Sci., 41, 992-1001 (2001). A New Approach to Near-Infrared Spectral Data Analysis Using Independent Component Analysis.
69. D. Broadhurst, R. Goodacre, A. Jones, J. J. Rowland, and D. B. Kell, Anal. Chim. Acta, 348, 71-86 (1997). Genetic Algorithms as a Method for Variable Selection in Multiple Linear Regression and Partial Least Squares Regression, with Applications to Pyrolysis Mass Spectrometry.
70. H. Martens, M. Høy, B. M. Wise, R. Bro, and P. B. Brockhoff, J. Chemom., 17, 153-165 (2003). Pre-Whitening of Data by Covariance-Weighted Pre-Processing.
71. J. A. Hageman, M. Streppel, R. Wehrens, and L. M. C. Buydens, J. Chemom., 17, 427-437 (2003). Wavelength Selection with Tabu Search.
72. J. M. Brenchley, U. Hörchner, and J. H. Kalivas, Appl. Spectrosc., 51(5), 689-699 (1997). Wavelength Selection Characterization for NIR Spectra.
73. S. L. Shew, Method and Apparatus for Determining Relative Ion Abundances in Mass Spectrometry Utilizing Wavelet Transforms. Patent #5,436,447, 1995.
74. X. Shao, L. Shao, and G. Zhao, Anal. Commun., 35, 135-137 (1998). Extraction of Extended X-ray Absorption Fine Structure Information from the Experimental Data Using the Wavelet Transform.
75. Y. Ding, T. Nanba, and Y. Miura, Phys. Rev. B: Condens. Matter, 58(21), 14279-14287 (1998). Wavelet Analysis of X-Ray Diffraction Pattern for Glass Structures.
76. D. Barache, J.-P. Antoine, and J. M. Dereppe, J. Magn. Reson., 128, 1-11 (1997). The Continuous Wavelet Transform, An Analysis Tool for NMR Spectroscopy.
77. P. Guillemain, R. Kronland-Martinet, and B. Martens, in Wavelet and Applications, Vol. 20, Y. Meyer, Ed., Masson and Springer-Verlag, Paris, 1992, pp. 38-60. Estimation of Spectral Lines with the Help of the Wavelet Transform - Applications in NMR Spectroscopy.
78. G. Neue, Solid State Nucl. Magn. Reson., 5, 305-314 (1996). Simplification of Dynamic NMR Spectroscopy by Wavelet Transforms.
79. F. G. Meyer and G. McCarthy, in Information Processing in Medical Imaging: 17th International Conference, IPMI 2001, Davis, California, USA, June 18-22, 2001, Proceedings, M. F. Insana and R. M. Leahy, Eds. Springer-Verlag, New York, 2001, pp. 232-238. Estimation of Baseline Drifts in fMRI.
80. H. Serrai, L. Senhadji, J. D. de Certaines, and J. L. Coatrieux, J. Magn. Reson., 124, 20-34 (1997). Time-Domain Quantification of Amplitude, Chemical Shift, Apparent Relaxation Time T*2, and Phase by Wavelet-Transform Analysis. Application to Biomedical Magnetic Resonance Spectroscopy.
81. U. L. Günther, C. Ludwig, and H. Rüterjans, J. Magn. Reson., 156, 19-25 (2002). WAVEWAT - Improved Solvent Suppression in NMR Spectra Employing Wavelet Transforms.
82. V. L. Martins, L. F. de Almeida, S. L. de Castro, R. K. H. Galvão, M. C. U. de Araújo, and E. C. da Silva, J. Chem. Inf. Comput. Sci., 43(6), 1725-1732 (2003). A Multiscale Wavelet Data Treatment for Reliable Localization of Inflection Points for Analytical Purposes.
83. R. A. DeVore, B. Jawerth, and B. J. Lucier, IEEE T. Inform. Theory, 38(2), 719-746 (1992). Image Compression Through Wavelet Transform Coding.
84. J. Le Moigne, Multi-Sensor Image Registration, Fusion and Dimension Reduction, 2005 Available: http://satjournal.tcom.ohiou.edu/issue03/ applications.html.
85. J. Le Moigne and I. Zavorin, in Use of Wavelets for Image Registration, Wavelet Applications VII, SPIE Aerosense 2000, Orlando, Florida, 2000.
86. J. M. Shapiro, IEEE T. Signal Proces., 41(12), 3445-3462 (1993). Embedded Image Coding Using Zerotrees of Wavelet Coefficients.
87. L. J. Chipman, T. M. Orr, and L. N. Graham, in Wavelet Applications in Signal and Image Processing III, SPIE, July 12-14, 1995, San Diego, California, Proceedings, A. F. Laine, M. A. Unser, and M. V. Wickerhauser, Eds., SPIE, the International Society for Optical Engineering, Bellingham, Massachusetts, 1995, pp. 208-219. Wavelets and Image Fusion.
88. F. Peyrin, M. Zaim, and R. Goutte, J. Math. Imaging Vis., 3, 105-121 (1993). Construction of Wavelet Decompositions for Tomographic Images.
89. H. Li, S. Manjunath, and S. K. Mitra, Graph. Model. Im. Proc., 57(3), 235-245 (1995). Multisensor Image Fusion Using the Wavelet Transform.
90. Z. Zhang and R. S. Blum, in Multisensor Image Fusion Using a Region-Based Wavelet Transform Approach, DARPA Image Understanding Workshop 1997, New Orleans, Louisiana, 1997; pp. 1447-1451.
91. A. K.-M. Leung, F.-T. Chau, J.-B. Gao, and T.-M. Shih, Chemom. Intell. Lab. Syst., 43, 69-88 (1998). Application of Wavelet Transform in Infrared Spectrometry: Spectral Compression and Library Search.
92. B. Walczak and D. L. Massart, Chemom. Intell. Lab. Syst., 38, 39-50 (1997). Wavelet Packet Transform Applied to a Set of Signals: A New Approach to the Best-Basis Selection.
93. K.-K. Li, F.-T. Chau, and A. K.-M. Leung, Chemom. Intell. Lab. Syst., 52, 135-143 (2000). Compression of Ultraviolet-Visible Spectrum with Recurrent Neural Network.
94. F.-T. Chau, J.-B. Gao, T.-M. Shih, and J. Wang, Appl. Spectrosc., 51(5), 649-659 (1997). Compression of Infrared Spectral Data Using the Fast Wavelet Transform Method.
95. L. Wei and L. Jinping, Chin. Sci. Bull., 42(10), 822-826 (1997). The Compression of IR Spectra by Using Wavelet Neural Network.
96. K. L. Peterson, in Reviews in Computational Chemistry, Vol. 16, K. B. Lipkowitz and D. B. Boyd, Eds., Wiley-VCH, New York, 2000, pp. 53-140. Artificial Neural Networks and Their Use in Chemistry.
97. K. J. Cho, T. A. Arias, J. D. Joannopoulos, and P. K. Lam, Phys. Rev. Lett., 71(12), 1808-1811 (1993). Wavelets in Electronic Structure Calculations.
98. M. F. Herman, Annu. Rev. Phys. Chem., 45, 83-111 (1994). Dynamics by Semiclassical Methods.
99. R. Kosloff, Annu. Rev. Phys. Chem., 45, 145-178 (1994). Propagation Methods for Quantum Molecular Dynamics.
100. H. Nakamura, Annu. Rev. Phys. Chem., 48, 299-328 (1997). Theoretical Studies of Chemical Dunamics: Overview of Some Functional Mechanisms.
101. T. A. Arias, Rev. Mod. Phys., 71(1), 267-311 (1999). Multiresolution Analysis of Electronic Structure: Semicardinal and Wavelet Bases.
102. D. Feller and E. R. Davidson, in Reviews in Computational Chemistry, Vol. 1, K. B. Lipkowitz and D. B. Boyd, Eds., VCH Publishers, Weinheim, Germany, 1990, pp. 1-43. Basis Sets for Ab Initio Molecular Orbital Calculations and Intermolecuiar Interactions.
103. T. A. Arias, K. J. Cho, J. D. Joannopoulos, P. K. Lam, and M. P. Teter, in Toward Teraflop Computing and New Grand Challenge Applications, R. K. Kalia and P. Vashishta, Eds., Nova Science Publishers, Inc., Hauppauge, New York, 1995, pp. 25-36. Wavelet-Transform Representation of the Electronic Structure of Materials.
104. S. Wei and M. Y. Chou, Phys. Rev. Lett., 76(15), 2650-2653 (1996). Wavelets in Self-Consistent Electronic Structure Calculations.
105. P. Fischer and M. Defranceschi, in Conceptual Trends in Quantum Chemistry, E. S. Kryachko and J. L. Calais, Eds., Kluwer Academic, Dordrecht, the Netherlands, 1994, pp. 227-247. The Wavelet Transform: A New Mathematical Tool for Quantum Chemistry.
106. S. Nagy and P. János, Int. J. Quantum Chem., 84, 523-529 (2001). Multiresolution Analysis of Density Operators, Electron Density, and Energy Functionals.
107. S. S. Iyengar and M. J. Frisch, J. Chem. Phys., 121(11), 5061-5070 (2004). Effect of Time-Dependent Basis Functions and Their Superposition Error on Atom-Centered Density Matrix Propagation (ADMP): Connections to Wavelet Theory of Multiresolution Analysis.
108. N. R. Kestner and J. E. Combariza, in Reviews in Computational Chemistry, Vol. 13, K. B. Lipkowitz and D. B. Boyd, Eds., Wiley-VCH, New York, 1999, pp. 99-132. Basis Set Superposition Errors: Theory and Practice.
109. J. P. Modisette, P. Nordlander, J. L. Kinsey, and B. R. Johnson, Chem. Phys. Lett., 250, 485-494 (1996). Wavelet Bases in Eigenvalue Problems in Quantum Mechanics.
110. P. Fischer and M. Defranceschi, Int. J. Quantum Chem., 45, 619-636 (1993). Looking at Atomic Orbitals Through Fourier and Wavelet Transforms.
111. P. Fischer and M. Defranceschi, in Wavelets: Theory, Algorithms and Applications, C. K. Chui, L. Montefusco, and L. Puccio, Eds., Academic Press, New York, 1994, pp. 495-506. Representation of the Atomic Hartree-Fock Equations in a Wavelet Basis by Means of the BCR Algorithm.
112. E. von Kitzingand E. Schmitt, THEOCHEM, 336, 245-259 (1995). Configurational Space of Biological Macromolecules as Seen by Semi-empirical Force Fields: Inherent Problems for Molecular Design and Strategies to Solve Them by Means of Hierarchical Force Fields.
113. R. J. Harrison, G. I. Fann, T. Yanai, Z. Gan, and G. Beylkin, J. Chem. Phys., 121(23), 11587-11598 (2004). Multiresolution Quantum Chemistry: Basic Theory and Initial Applications.
114. T. Yanai, G. I. Fann, Z. Gan, R. J. Harrison, and G. Beylkin, J. Chem. Phys., 121(14), 6680-6688 (2004). Multiresolution Quantum Chemistry in Multiwavelet Bases: Hartree-Fock Exchange.
115. T. Yanai, G. I. Fann, Z. Gan, R. J. Harrison, and G. Beylkin, J. Chem. Phys., 121(7), 2866-2876 (2004). Multiresolution Quantum Chemistry in Multiwavelet Bases: Analytic Derivatives for Hatree-Fock and Density Functional Theory.
116. L. B. Kier and L. H. Hall, Molecular Connectivity In Chemistry and Drug Research, Academic Press, New York, 1976.
117. L. B. Kier and L. H. Hall, Molecular Connectivity in Structure-Activity Analysis, John Wiley, London, 1986.
118. L. B. Kier, L. H. Hall, W. J. Murray, and M. Randic, J. Pharm. Sci., 64(12), 1971-1974 (1975). Molecular Connectivity. I: Relationship to Nonspecific Local Anesthesia.
119. C. Hansch and A. Leo, Exploring QSAR, American Chemical Society, Washington, D.C., 1995.
120. M. Cocchi, R. Seeber, and A. Ulrici, Chemom. Intell. Lab. Syst., 57, 97-119 (2001). WPTER: Wavelet Packet Transform for Efficient Pattern Recognition of Signals.
121. L. I. Nord and S. P. Jacobsson, Chemom. Intell. Lab. Syst., 44, 153-160 (1998). A Novel Method for Examination of the Variable Contribution to Computational Neural Network Models.
122. Y. Mallet, D. Coomans, J. Kautsky, and O. de Vel, IEEE T. Pattern Anal., 19(10), 1058-1066 (1997). Classification Using Adaptive Wavelets for Feature Extraction.
123. P. Wunsch and A. F. Laine, Pattern Recogn., 28(8), 1249 (1995). Wavelet Descriptors for Multiresolution Recognition of Handprinted Characters.
124. O. E. d. Noord, Chemom. Intell. Lab. Syst., 23, 65-70 (1994). The Influence of Data Preprocessing on the Robustness and Parsimony of Multivariate Calibration Models.
125. Y. Mallet, D. Coomans, and O. de Vel, Chemom. Intell. Lab. Syst., 35, 157-173 (1996). Recent Development in Discriminant Analysis on High Dimensional Spectral Data.
126. M. Bos and J. A. M. Vrielink, Chemom. Intell. Lab. Syst., 23, 115-122 (1994). The Wavelet Transform for Pre-processing IR Spectra in the Identification of Mono- and Di-substituted Benzenes.
127. B. Walczak, E. Bouveresse, and D. L. Massart, Chemom. Intell. Lab. Syst., 36, 41-51 (1997). Standardization of Near-Infrared Spectra in the Wavelet Domain.
128. B. Walczak, B. van den Bogaert, and D. L. Massart, Anal. Chem., 68, 1742-1747 (1996). Application of Wavelet Packet Transform in Pattern Recognition of Near-IR Data.
129. P. D. B. Harrington, A. Urbas, and C. Wan, Anal. Chem., 72, 5004-5013 (2000). Evaluation of Neural Network Models with Generalized Sensitivity Analysis.
130. C. M. Breneman, N. Sukumar, K. P. Bennett, M. J. Embrechts, C. M. Sundling, and L. Lockwood, in QSAR In Vivo: American Chemical Society National Meeting, American Chemical Society, Washington, D.C., 2000. Wavelet Representations of Molecular Electronic Properties: Applications in ADME, QSPR, and QSAR.
131. L. Lockwood. 1. Effects of a Trimethylsilyl Substituent on the Photochemical Rearrangement of 2,5-cyclohexadienones. 2. Development and Implementation of Novel Electron Density Derived Molecular Surface Descriptors. Ph.D. dissertation, Rensselaer Polytechnic Institute, Troy, New York, 2002.
132. C. M. Breneman and M. Rhem, J. Comput. Chem., 18(2), 182-197 (1997). A QSPR Analysis of HPLC Column Capacity Factors for a set of High-Energy Materials Using Electronic Van der Waals Surface Property Descriptors Computed by the Transferable Atom Equivalent Method.
133. R. F. W. Bader, Atoms in Molecules: A Quantum Theory, Oxford Press, Oxford, United Kingdom, 1990.
134. J. S. Murray and P. Politzer, in Theoretical Organic Chemistry, Vol. 5, C. Párkányi, Ed., Elsevier Science Publishers BV, Amsterdam, the Netherlands, 1998, pp. 189-202. Average Local Ionization Energies: Significance and Applications.
135. P. Politzer and D. G. Truhlar, Chemical Applications of Atomic and Molecular Electrostatic Potential, Plenum Press, New York, 1981.
136. P. Politzer, N. Sukumar, K. Jayasuriya, and S. Ranganathan, J. Am. Chem. Soc., 110, 3425-3430 (1988). A Computational Evaluation and Comparison of Nitramine Properties.
137. J. S. Murray, N. Sukumar, S. Ranganathan, and P. Politzer, Int. J. Quantum Chem., 37(5), 611-629 (1990). A Computational Analysis of the Electrostatic Potentials and Relative Bond Strengths of Hydrazine and Some of its 1,1-Dimethyl Derivatives.
138. C. M. Breneman and M. Martinov, in Molecular Electrostatic Potentials: Concepts and Applications, Vol. 3, J. S. Murray and K. Sen, Eds., Elsevier, Amsterdam, the Netherlands, 1996, pp. 143-179. The Use of Electrostatic Potential Fields in QSAR and QSPR.
139. K. Fukui, T. Yonezawa, and C. Nagata, J. Chem. Phys., 27(6), 1247-1259 (1957). MO-Theoretical Approach to the Mechanism of Charge Transfer in the Process of Aromatic Substitutions.
140. K. Fukui, Theory of Orientation and Stereoselection, Springer-Verlag, Berlin, Germany, 1975.
141. R. G. Parr and W. Yang, J. Am. Chem. Soc., 106, 4049-4050 (1984). Density-Functional Approach to the Frontier-Electron Theory of Chemical Rectivity.
142. R. G. Parr and W. Yang, Density-Functional Theory of Atoms and Molecules, Oxford University Press, New York, 1989.
143. K. Hasegawa and K. Funatsu, SAR QSAR Environ. Res., 11(3-4), 189-209 (2000). Partial Least-Squares Modeling and Genetic Algorithm Optimization in Quantitative Structure-Activity Relationships.
144. K. Hasegawa, Y. Miyashita, and K. Funatsu, J. Chem. Inf. Comput. Sci., 37(2), 306-310 (1997). GA Strategy for Variable Selection in QSAR Studies: GA-Based PLS Analysis of Calcium Channel Antagonists.
145. M. Ozdemir, Evolutionary Computing for Feature Selection and Predictive Data Mining. Ph.D. dissertation, Rensselaer Polytechnic Institute, Troy, New York, 2002.
146. R. Garg, S. P. Gupta, H. Gao, M. S. Babu, A. K. Debnath, and C. Hansch, Chem. Rev., 99, 3525-3691 (1999). Comparative Quantitative Structure-Activity Relationship Studies on Anti-HIV Drugs.
147. B. Debska, B. Guzowska-Swider, and D. Carbol-Bass, J. Chem. Inf. Comput. Sci., 40, 330-338 (2000). Automatic Generation of Knowledge Base from Infrared Spectral Database for Substructure Recognition.
148. C. Cai and P. d. B. Harrington, Anal. Chem., 71, 4134-4141 (1999). Prediction of Substructure and Toxicity of Pesticides with Temperature Constrained-Cascade Correlation Network from Low-Resolution Mass Spectra.
149. M. Jalali-Heravi and M. H. Fatemi, J. Chromatogr. A, 825, 161-169 (1998). Prediction of Flame Ionization Detector Response Factors Using an Artificial Neural Network.
150. C. M. R. Ginn, D. B. Turner, and P. Willett, J. Chem. Inf. Comput. Sci., 37, 23-37 (1997). Similarity Searching in Files of Three-Dimensional Chemical Structures: Evaluation of the EVA Descriptor and Combination of Rankings Using Data Fusion.
151. A.M. Ferguson, T. W. Heritage, P. Jonathon, S. E. Pack, L. Phillips, J. Rogan, and P. J. Snaith, J. Comput. Aided Mol. Des., 11, 143-152 (1997). EVA: A New Theoretically Based Molecular Descriptor for Use in QSAR/QSPR Analysis.
152. T. W. Heritage, A. M. Ferguson, D. B. Turner, and P. Willett, Perspect. Drug Discov., 9-11, 381-398 (1998). EVA: A Novel Theoretical Descriptor for QSAR Studies.
153. J. Trygg and S. Wold, Chemom. Intell. Lab. Syst., 42, 209-220 (1998). PLS Regression on Wavelet Compressed NIR Spectra.
154. M. Nikolaou and P. Vuthandam, AIChE J., 44(1), 141-150 (1998). FIR Model Identification: Parsimony Through Kernel Compression with Wavelets.
155. E. R. Collantes, R. Duta, W. J. Welsh, W. L. Zielinski, and J. Brower, Anal. Chem., 69, 1392-1397 (1997). Preprocessing of HPLC Trace Impurity Patterns by Wavelet Packets for Pharmaceutical Fingerprinting Using Artificial Neural Networks.
156. S. Maldonado-Bascón, S. Al-Khalifa, and F. López-Ferreras, in Computational Methods in Neural Modeling: Seventh International Conference, IWANN 2003, Mao, Spain, June 3-6, 2003, Proceedings, Vol. 2687, J. Méra and J. R. Alvarez, Eds., Springer-Verlag, New York, 2003, pp. 798-805. Feature Reduction Using Support Vector Machines for Binary Gas Detection.
157. P. Althainz, J. Goschnick, S. Ehrmann, and H. J. Ache, Sensor. Actuat. B, 33, 72-76 (1996). Multisensor Microsystem for Contaminants in Air.
158. X. Zhang, J. Qi, R. Zhang, M. Liu, Z. Hu, H. Xue, and B. Fan, Comput. Chem. (Oxford), 25, 125-133 (2001). Prediction of Programmed-Temperature Retention Values of Naphthas by Wavelet Neural Networks.
159. L. Liu and Q.-X. Guo, J. Chem. Inf. Comput. Sci., 39, 133-138 (1999). Wavelet Neural Network and Its Application to the Inclusion of beta-Cyclodextrin with Benzene Derivatives.
160. C. Yiyu, C. Minjun, and W. J. Welsh, J. Chem. Inf. Comput. Sci., 43(6), 1959-1965 (2003). Fractal Fingerprinting of Chromatographic Profiles Based on Wavelet Analysis and Its Application to Characterize the Quality Grade of Medicinal Herbs.
161. M. Köküer, F. Murtagh, N. D. McMillan, S. Riedel, B. O'Rourke, K. Beverly, A. T. Augousti, and J. Mason, J. Chem. Inf. Comput. Sci., 43, 587-594 (2003). A Wavelet, Fourier and PCA Data Analysis Pipeline: Application to Distinguishing Mixtures of Liquids.
162. J. Zhao, X. W. Yang, J. P. Li, and Y. Y. Tang, in Wavelet Analysis and Its Applications: Second International Conference, WAA 2001, Hong Kong, China, December 18-20, 2001, Proceedings, Vol. 2251, Y. Y. Tang, M. V. Wickerhauser, P. C. Yuen, and C. H. Li, Eds., Springer-Verlag, New York, 2002, pp. 424-429. DNA Sequences Classification Based on Wavelet Packet Analysis.
163. G. V. Gkoutos, H. Rzepa, R. M. Clark, O. Adjei, and H. Johal, J. Chem. Inf. Comput. Sci., 43(5), 1342-1355 (2003). Chemical Machine Vision: Automated Extraction of Chemical Metadata from Raster Images.