Pattern discovery in bioinformatics: Theory algorithms

Pattern Discovery in Bioinformatics: Theory Algorithms

Volumn , Issue , 2007, Pages 1-526

  Parida, Laxmi ^a  

^a IBM T J WATSON RESEARCH CENTER   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 85054765964     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1201/9781420010732     Document Type: Book

References (124)

1. A. Amir, A. Apostolico, G. M. Landau, and G. Satta. Efficient text fingerprinting via parikh mapping. Journal of Discrete Algorithms, 1(5-6):409 – 421, 2003.
2. M. Alexandersson, S. Cawley, and L. Pachter. SLAM—cross-species gene finding and alignment with a generalized pair hidden Markov model. 13:496–502, 2003.
3. A. Apostolico, M. Comin, and L. Parida. Conservative extraction of over-represented extensible motifs. ISMB (Supplement of Bioinformatics), 21:9–18, 2005.
4. Alberto Apostolico, Matteo Comin, and Laxmi Parida. Varun: Discovering extensible motifs under saturation constraints. Preprint, 2007.
5. W. Ao, J. Gaudet, W.J. Kent, S. Muttumu, and S.E Mango. Environmentally induced foregut remodeling by pha-4/foxa and daf-12/nhr. Science, 305(5691):1743–1746, 2004.
6. A. Apostolico, C. Iliopoulos, G. M. Landau, B. Schieber, and U. Vishkin. Parallel construction of a suffix tree with applications. Algorithmica, 3:347–365, 1988.
7. T.S. Anantharaman, B. Mishra, and D.C. Schwartz. Genomics via optical mapping II: Ordered restriction maps. Journal of Computational Biology, 4(2):91–118, 1997.
8. A. Apostolico and L. Parida. Incremental paradigms for motif discovery. Journal of Computational Biology, 11(4):15–25, 2004.
9. S. Böcker. Sequencing from compomers: Using mass spectrometry for DNA de novo sequencing of 200+ nt. Journal of Computational Biology, 11(6):1110–1134, 2004.
10. A. Blumer, J. Blumer, A. Ehrenfeucht, D. Haussler, M.T. Chen, and J. Seiferas. The smallest automaton recognizing the sub-words of a text. Theoretical Computer Science, pages 31–55, 1985.
11. John W.S. Brown, Gillian P. Clark, David J. Leader, Craig G. Simpson, and Todd Lowe. Multiple snoRNA gene clusters from arabidopsis. RNA, 7:1817–1832, 2001.
12. T. L. Bailey and C. Elkan. Fitting a mixture model by expectation maximization to discover motifs in biopolymers. In Proceedings of the Second International Conference on Intelligent Systems for Molecular Biology, pages 28–36. AAAI Press, 1994.
13. N.E. Buchler, U. Gerland, and T. Hwa. On Schemes of Combinatorial Transcription Logic. PNAS, 100(9):5136–5141, 2003.
14. S. K. Bryan, M. E. Hagensee, and R. E. Moses. DNA poly-merase III requirement for repair of DNA damage caused by methyl methanesulfonate and hydrogen peroxide. In Journal of Bacteriology, volume 16, pages 4608–4613. ACM Press, 1987.
15. K. Booth and G. Leukar. Testing for the consecutive ones property, interval graphs, and graph planarity using PQ-tree algorithms. Journal of Computer and Syste
16. m Sciences, 13:335–379, 1976.
17. B. Balasubramanian, C. V. Lowry, and R. S. Zitomer. The Rox1 repressor of the saccharomyces cerevisiae hypoxic genes is a specific DNA-binding protein with a high-mobility-group motif. Mol Cell Biol, 13(10):6071–6178, 1993.
18. M.-P. Bal, F. Mignosi, A. Restivo, and M. Sciortino. Forbidden words in symbolic dynamics. Advances in Applied Mathematics, 25:163–193, 2002.
19. K.H. Burns, M.M. Matzuk, A. Roy, and W. Yan. Tektin3 encodes an evolutionarily conserved putative testicular micro tubules-related protein expressed preferentially in male germ cells. In Molecular Reproduction and Development, volume 67, pages 295–302. ACM Press, 2004.
20. N.H. Bshouty. Exact Learning Boolean Functions via the Monotone Theory. Information and Computation, Vol. 123(1):146– 153, 1995.
21. Jeremy Buhler and Martin Tompa. Finding motifs using random projections. In Journal of Computational Biology, volume 9(2), pages 225—242, 2002.
22. G. Brightwell and P. Winkler. Counting linear extensions. In Order, pages 225–242, 1991.
23. G. Brightwell and P. Winkler. Counting linear extensions is #P-complete. In Proc. 23rd ACM Symposium on the Theory of Computing (STOC), pages 175–181, 1991.
24. D. Y.-H. Chiang. Computational and Experimental Analyses of Promoter Architecture in Yeasts. PhD thesis, University of California, Berkeley, Spring 2005.
25. W. Cai, J. Jing, B. Irvine, L. Ohler, E. Rose, H. Shizua, U. J. Kim, M. Simon, T. Anantharaman, B. Mishra, and D. C. Schwartz. High-resolution restriction maps of bacterial artificial chromosomes constructed by optical mapping. Proc. Natl. Acad. Sci. USA, 95:3390–3395, 1998.
26. T. H. Cormen, C. E. Leiserson, and R. L. Rivest. Introduction to Algorithms. The MIT Press, Cambridge, Massachusetts, 1990.
27. Joseph F. Contrera, Philip MacLaughlin, Lowell H. Hall, and Lemont B. Kier. QSAR modeling of carcinogenic risk using discriminant analysis and topological molecular descriptors. Current Drug Discovery Technologies, Vol. 2(2):55–67, 2005.
28. A. Chattaraj and L. Parida. An inexact suffix tree based algorithm for extensible pattern discovery. Theoretical Computer Science, (1):3–14, 2004.
29. Matteo Comin and Laxmi Parida. Subtle motif discovery for detection of DNA regulatory sites. Asia Pacific Bioinformatics Conference, pages 95–104, 2007.
30. F. Coulon and M. Raffinot. Fast algorithms for identifying maximal common connected sets of interval graphs. Proceedings of Algorithms and Computational Methods for Biochemical and Evolutionary Networks (CompBioNets), 2004.
31. O. Dror, H. Benyamini, R. Nussinov, and H. J. Wolfson. Multiple structural alignment by secondary structures: Algorithm and applications. Protein Science, 12(11):2492–2507, 2003.
32. [DFK] M. Dyer, A. Frieze, and R. Kannan. A random polynomial-time algorithm for approximating the volume of convex bodies. In Journal of the ACM (JACM), number 1.
33. R.O. Duda and P. E. Hart. Pattern Classification and Scene Analysis. John Wiley & Sons, Menlo Park, California, 1973.
34. G. Didier. Common intervals of two sequences. In Proc. of the Third Wrkshp. on Algorithms in Bioinformatics, volume 2812 of Lecture Notes in Bioinformatics, pages 17–24. Springer-Verlag, 2003.
35. Dannie Durand and David Sankoff. Tests for gene clustering. Journal of Computational Biology, 10(3-4):453–482, 2003.
36. T. Dandekar, B. Snel, M. Huynen, and P. Bork. Conservation of gene order: a fingerprint of proteins that physically interact. Trends Biochem. Sci., 23:324–328, 1998.
37. Revital Eres, Gad M. Landau, and Laxmi Parida. A combinatorial approach to automatic discovery of cluster-patterns. In Proc. of WABI, September 15-20, 2003.
38. Eleazar Eskin and Pavel Pevzner. Finding composite regulatory patterns in DNA sequences. In Bioinformatics, volume 18, pages 354–363, 2002.
39. William Feller. An Introduction to Probability Theory and its Applications. Wiley, 1968.
40. D.H. Fisher. Knowledge Acquisition via Incremental Conceptual Clustering. Machine Learning, Vol. 2(2):139–172, 1987.
41. + 99] Aris Floratos, Isidore Rigoutsos, Laxmi Parida, Gustavo Stolovitzky, and Yuan Gao. Sequence homology detection through large-scale pattern discovery. In Proceedings of the Annual Conference on Computational Molecular Biology (RE-COMB99), pages 209–215. ACM Press, 1999.
42. + 01] S. Giglio, K. W. Broman, N. Matsumoto, V. Calvari, G. Gimelli, T. Neuman, H. Obashi, L. Voullaire, D. Larizza, R. Giorda, J. L. Weber, D. H. Ledbetter, and O. Zuffardi. Olfactory receptor-gene clusters, genomic-inversion polymorphisms, and common chromosme rearrangements. Am. J. Hum. Genet., 68(4):874– 883, 2001.
43. M.R. Garey and D.S. Johnson. Computers and Intractability: A Guide to the Theory of NP-Completeness. W.H. Freeman and Co., San Francisco, 1979.
44. H. H. Gan, S. Pasquali, and T. Schlick. Exploring the repertoire of RNA secondary motifs using graph theory: implications for RNA design. Nucleic Acids Research, 31(11):2926–2943, 2003.
45. C.T. Harbison et al. Transcriptional Regulatory Code of a Eukaryotic Genome. Nature, 431:99–104, Sep 2004.
46. J. D. Hughes, P. W. Estep, S. Tavazoie, and G. M. Church. Computational identification of cis-regulatory elements associated with groups of functinally related genes in Saccharomyces cerevisiae. J Molec. Bio., 296:1205–1214, 2000.
47. X. He and M.H. Goldwasser. Identifying conserved gene clusters in the presence of orthologous groups. In Proceedings of the Annual Conference on Computational Molecular Biology (RE-COMBo4), pages 272–280. ACM Press, 2004.
48. G. Z. Hertz and G. D. Stormo. Identifying DNA and protein patterns with statistically significant alignments of multiple sequences. Bioinformatics, 15:563–577, 1999.
49. Rose Hoberman, David Sankoff, and Dannie Durand. The statistical significance of max-gap clusters. Lecture Notes in Computer Science, 3388/2005, 2005.
50. S. Istrail and E.H. Davidson. Logic functions of the genomic cis-regulatory code. PNAS, 102(14):4954–4959, Apr 2005.
51. A. Inokuchi, T. Washio, and H. Motoda. Complete mining of frequent patterns from graphs: Mining graph data. Machine Learning, 50(3):321–354, 2003.
52. D. Kihara and M. Kanehisa. Tandem clusters of membrane proteins in complete genome sequences. Genome Research, 10:731– 743, 2000.
53. Z. M. Kedem, G. M. Landau, and K. V. Palem. Parallel suffix-prefix matching algorithm and application. SIAM Journal of Computing, 25(5):998–1023, 1996.
54. R. Karp, R. Miller, and A. Rosenberg. Rapid identification of repeated patterns in strngs, arrays and trees. In Symposium on Theory of Computing, volume 4, pages 125–136, 1972.
55. Keich and Pevzner. Finding motifs in the twilight zone. In Annual International Conference on Computational Molecular Biology, pages 195–204, Apr, 2002.
56. Uri Keich and Pavel Pevzner. Subtle motifs: defining the limits of motif finding algorithms. In Bioinformatics, volume 18, pages 1382–1390, 2002.
57. M. Kellis, N. Patterson, M. Endrizzi, B. Birren, and E. S. Lander. Sequencing and comparison of yeast species to identify genes and regulatory elements. Nature, 423:241–254, May 2003.
58. Md Enamul Karim, Laxmi Parida, and Arun Lakhotia. Using permutation patterns for content-based phylogeny. In Pattern Recognition in Bioinformatics, volume 4146 of Lecture Notes in Bioinformatics, pages 115–125. Springer-Verlag, 2006.
59. C. E. Lawrence, S. F. Altschul, M. S. Boguski, J. S. Liu, A. F. Neuwald, and J. C. Wootton. Detecting subtle sequence signals: A Gibbs sampling strategy for multiple alignment. Science, 262:208–214, Oct, 1993.
60. M. Levine and E.H. Davidson. Gene regulatory networks for development. PNAS, 102(4):4936–4942, Apr 2005.
61. Arun Lakhotia, Md Enamul Karim, Andrew Walenstein, and Laxmi Parida. Malware phylogeny using maximal π-patterns. In EICAR, 2005.
62. A. V. Lukashin, M.E. Lakashev, and R. Fuchs. Topology of gene expression networks as revealed by data mining and modeling. Bioinformatics, 19(15):1909–1916, 2003.
63. M. Y. Leung, G. M. Marsh, and T. P. Speed. Over and un-derrepresentation of short DNA words in herpesvirus genomes. Journal of Computational Biology, 3:345–360, 1996.
64. Gad Landau, Laxmi Parida, and Oren Weimann. Using PQ trees for comparative genomics. In Proc. of the Symp. on Comp. Pattern Matching, volume 3537 of Lecture Notes in Computer Science, pages 128–143. Springer-Verlag, 2005.
65. C. E. Lawrence and A. A. Reilly. An expectaion maximization (EM) algorithm for the identification and characterization of common sites in unaligned biopolymer sequences. Proteins: Structure, Function and Genetics, 7:41–51, 1990.
66. J. G. Lawrence and J. R. Roth. Selfish operons: Horizontal transfer may drive the evolution of gene clusters. Genetics, 143:1843–1860, 1996.
67. H. Li and W. Wang. Dissecting the transcription networks of a cell using computational genomics. Current Opinion in Genetics and Development, 13:611–616, 2003.
68. Aurlien Mazurie, Samuel Bottani, and Massimo Vergassola. An evolutionary and functional assessment of regulatory network motifs. Genome Biolgy, 6(4), 2005.
69. M. Habib M. Chein and M.C Maurer. Partitive hypergraphs. Discrete Mathematics, 37:35–50, 1981.
70. R.S. Michalski. Knowledge acquisition through conceptual clustering: A theoretical framework and algorithm for partitioning data into conjunctive concepts. International Journal of Policy Analysis and Information Systems, Vol. 4:219–243, 1980.
71. H. Mannila and C. Meek. Global Partial Orders from Sequential Data. In Proc. KDD’00, pages 161–168, 2000.
72. S.C. Madeira and A.L. Oliveira. Biclustering algorithms for biological data analysis: A survey. IEEE/ACM TCBB, 1:24– 45, 2004.
73. E. M. Marcott, M. Pellegrini, H. L. Ng, D. W. Rice, T. O. Yeates, and D. Eisenberg. Detecting protein function and protein-protein interactions. Science, 285:751–753, 1999.
74. [MSOI+ 02] R. Milo, S. Shen-Orr, S. Itzkovitz, N. Kashtan, D. Chklovskii, and U. Alon. Network motifs: Simple building blocks of complex networks. Science, 298:824–827, 2002.
75. T. Murata. Graph mining approaches for the discovery of web communities. Proceedings of the International Workshop on Mining Graphs, Trees and Sequences, pages 79–82, 2003.
76. R. Overbeek, M. Fonstein, M. Dsouza, G. D. Pusch, and N. Maltsev. The use of gene clusters to infer functional coupling. Proc. Natl. Acad. Sci. USA, 96(6):2896–2901, 1999.
77. H. Ogata, W. Fujibuchi, and S. Goto. A heuristic graph comparison algorithm and its application to detect functionally related enzyme clusters. Nucleic Acids Res, 28:4021–4028, 2000.
78. R. J. Parikh. On context-free languages. J. Assoc. Comp. Mach., 13:570–581, 1966.
79. L. Parida. A uniform framework for ordered restriction map problems. Journal of Computational Biology, 5(4):725–739, 1998.
80. L. Parida. On the approximability of physical map problems using single molecule methods. Procceedings of Discrete Mathematics and Theoretical Computer Science (DMTCS 99), pages 310–328, 1999.
81. L. Parida. A PQ framework for reconstructions of common ancestors & phylogeny. In RECOMB Satellite Workshop on Comparative Genomics, LNBI, volume 4205, pages 141–155, 2006.
82. Laxmi Parida. Discovering topological motifs using a compact notation. Journal of Computational Biology, 14(3):46–69, 2007.
83. Laxmi Parida. Gapped permutation pattern discovery for gene order comparisons. 14(1):46–56, 2007.
84. A.G. Pederson, P. Baldi, Y. Chauvin, and S. Brunak. The biology of eukaryotic promoter prediction: A review. Computers and Chemistry, 23:191–207, 1999.
85. N. Pisanti, M. Crochemore, R. Grossi, and M.-F. Sagot. Bases of motifs for generating repeated patterns with wild cards. IEEE/ACM Transaction on Computational Biology and Bioinformatics, 2(1):40–50, 2005.
86. L. Parida and D. Geiger. Mass estimation of DNA molecules & extraction of ordered restriction maps in optical mapping imagery. Algorithmica, (2/3):295–310, 1999.
87. L. Parida and N. Ramakrishnan. Redescription Mining: Structure Theory and Algorithms. In Proc. AAAI’05, pages 837–844, July 2005.
88. + 00] L. Parida, I. Rigoutsos, A. Floratos, D. Platt, and Y. Gao. Pattern discovery on character sets and real-valued data: Linear bound on irredundant motifs and an efficient polynomial time algorithm. In Proceedings of the eleventh ACM-SIAM Symposium on Discrete Algorithms (SODA), pages 297–308. ACM Press, 2000.
89. Alkes Price, Sriram Ramabhadran, and Pavel Pevzner. Finding subtle motifs by branching from sample strings. In Bioinformatics, number 1, pages 149–155, 2003.
90. H. Prüfer. Neuer beweis eines satzes über permutationen. Arch. Math. Phys, 27:742–744, 1918.
91. P. A. Pevzner and S.-H. Sze. Combinatorial approaches to finding subtle signals in DNA sequences. In Proceedings of the Eighth International Conference on Intelligent Systems for Molecular Biology, pages 269–278. AAAI Press, 2000.
92. Y. Pilpel, P. Sudarsanam, and G.M. Church. Identifying regulatory networks by combinatorial analysis of promoter elements. Nature Genetics, 29:153–159, Oct 2001.
93. L. Parida and R. Zhou. Combinatorial pattern discovery approach for the folding trajectory analysis of a β-hairpin. PLoS Computational Biology, 1(1), 2005.
94. S. Rajasekaran, S. Balla, and C.-H Huang. Exact algorithms for planted motif problems. Journal of Computational Biology, 12(8):1117–1128, 2005.
95. + 04] N. Ramakrishnan, D. Kumar, B. Mishra, M. Potts, and R.F. Helm. Turning CARTwheels: An Alternating Algorithm for Mining Redescriptions. In Proc. KDD’04, pages 266–275, Aug 2004.
96. Naren Ramakrishnan and Laxmi Parida. Modeling the combinatorial control of transcription using partial order motifs and their redescriptions. Preprint, 2007.
97. A. Reményi, H.R. Schöler, and M. Wilmanns. Combinatorial control of gene expression. Nature Structural and Molecular Biology, 11(4):812–815, Sep 2004.
98. M. F. Sagot. Spelling approximate repeated or common motifs using a suffix tree. Latin 98: Theoretical Informatics, Lecture Notes in Computer Science, 1380:111–127, 1998.
99. I. Simon, J. Barnett, N. Hannett, C. T. Harbison, N. J. Rinaldi, T. L. Volkert, J. J. Wyrick, J. Zeitlinger, D. K. Gifford, T. S. Jaakkola, and R. A. Young. Serial regulation of transcriptional regulators in the yeast cell cycle. Cell, 106:697–708, 2001.
100. A. Samad, W. W. Cai, X. Hu, B. Irvin, J. Jing, J. Reed, X. Meng, J. Huang, E. Huff, B. Porter, A. Shenker, T. Anantharaman, B. Mishra, V. Clarke, E. Dimalanta, J. Edington, C. Hiort, R. Rabbah, J. Skiadas, and D. Schwartz. Mapping the genome one molecule at a time – optical mapping. Nature, 378:516–517, 1997.
101. B. Snel, G Lehmann, P Bork, and M A Huynen. A web-server to retrieve and display repeatedly occurring neighbourhood of a gene. Nucleic Acids Research, 28(18):3443–3444, 2000.
102. J. L. Siefert, K. A. Martin, F. Abdi, W. R. Widger, and G. E. Fox. Conserved gene clusters in bacterial genomes provide further support for the primacy of RNA. J. Mol. Evol., 45:467–472, 1997.
103. S.S. Shen-Orr, R. Milo, S. Mangan, and U. Alon. Network motifs in the transcriptional regulation network of Escherichia coli. Nature Genetics, 31:64–68, 2002.
104. T. Schmidt and J. Stoye. Quadratic time algorithms for finding common intervals in two and more sequences. CPM, LNCS 3109:347–358, 2004.
105. E. Segal and R. Sharan. A discriminative model for identifying spatial cis-regulatory modules. JCB, 12(6):822–834, 2005.
106. A.D. Smith, P. Sumazin, D. Das, and M.Q. Zhang. Mining chip-chip data for transcription factor and cofactor binding sites. Bioinformatics, 21 (Suppl1):403–412, 2005.
107. [SSR+ 03] E. Segal, M. Shapira, A. Regev, D. Pe’er, D. Botstein, D. Koller, and N. Friedman. Module networks: Identifying regulatory modules and their condition-specific regulators from gene expression data. Nature Genetics, 34(2):166–176, June 2003.
108. G. D. Stormo. Computer methods for analyzing sequence recognition of nucleic acids. Annual Review of Biophysics and Biophysical Chemistry, 17:241–263, 1988.
109. J. Tamames, G. Casari, C. Ouzounis, and A. Valencia. Conserved clusters of functionally related genes in two bacterial genomes. J. Mol. Evol., 44:66–73, 1997.
110. K. Tomii and M. Kanehisa. A comparative analysis of ABC transporters in complete microbial genomes. Genome Res, 8:1048–1059, 1998.
111. [TKT+ 94] S. Taguchi, S. Kojima, M. Terabe, K. I. Miura, and H. Momose. Comparative studies on primary structures and inhibitory properties of subtilisintrypsin inhibitors from streptomyces. Eur J. Biochem., 220:911–918, 1994.
112. Martin Tompa, Nan Li, Timothy L. Bailey, George M. Church, Bart De Moor, Eleazar Eskin, Alexander V. Favorov, Martin C. Frith, Yutao Fu, W. James Kent, Vsevolod J. Makeev, Andrei A. Mironov, William Stafford Noble, Giulio Pavesi, Graziano Pesole, Mireille Rgnier, Nicolas Simonis, Saurabh Sinha, Gert Thijs, Jacques van Helden, Mathias Vandenbogaert, Zhiping Weng, Christopher Workman, Chun Ye, and Zhou Zhu. Assessing computational tools for the discovery of transcription factor binding sites. Nature Biotechnology, 23:137–144, 2005.
113. T. Uno and M. Yagiura. Fast algorithms to enumerate all common intervals of two permutations. Algorithmica, 26(2):290– 309, 2000.
114. A. Volbeda, M. H. Charon, C. Piras, E. C. Hatchikian, M. Frey, and J. C. Fontecilla-Camps. Crystal structure of the nickel-iron hydrogenase from desulfovibrio gigas. Nature, 373:580–587, 1995.
115. Andrew J. Viterbi. Error bounds for convolutional codes and an asymptotically optimum decoding algorithm. In IEEE Transactions on Information Theory, volume 13(2), pages 260–269, 1967.
116. R.E. Valdes-Perez, V. Pericliev, and F. Pereira. Concise, intelligible, and approximate profiling of multiple classes. International Journal of Human-Computer Studies, Vol. 53(3):411–436, 2000.
117. M.S. Waterman, R. Aratia, and D.J. Galas. Pattern recognition in several sequences: Consensus and alignment. Bulletin of Mathematical Biology, 46(4):515–527, 1984.
118. M.S. Waterman. An Introduction to Computational Biology: Maps, Sequences and Genomes. Chapman Hall, 1995.
119. H. Watanabe, H. Mori, T. Itoh, and T. Gojobori. Genome plasticity as a paradigm of eubacteria evolution. J. Mol. Evol., 44:S57–S64, 1997.
120. S. Wuchty, Z.N. Oltvai, and A-L Barabasi. Evolutionary conservation of motif constituents in the yeast protein interactin networks. Nature Genetics, 35(2):176–179, 2003.
121. M.J. Zaki. Mining non-redundant association rules. DMKD, 9(3):223–248, 2004.
122. Lan V Zhang, Oliver D King, Sharyl L Wong, Debra S Goldberg, Amy HY Tong, Guillaume Lesage, Brenda Andrews, Howard Bussey, Charles Boone, and Frederick P Roth. Motifs, themes and thematic maps of an integrated saccharomyces cerevisiae interaction network. Journal of Biology, Vol. 4(2), 2005.
123. Ruhong Zhou, Laxmi Parida, Kush Kapila, and Sudhir Mudur. PROTERAN: Animated terrain evolution for visual analysis of patterns in protein folding trajectory. Bioinformatics, 23(1):99– 106, 2007.
124. J. Zhu and M.Q. Zhang. SCPD: A promoter database of the yeast saccharomyces cerevisiae. Bioinformatics, 15:607–611, 1999.