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A Portrait of State-of-the-Art Research at the Technical University of Lisbon pp 295–309Cite as

Bioinformatics: A New Approach for the Challenges of Molecular Biology

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Abstract

We describe the research being undertaken by the ALGOS/KDBIO and Biological Sciences groups of Instituto Superior Técnico on the field of bioinformatics and computational biology, with emphasis on the efforts under way to develop new approaches, methods and algorithms for the determination of gene regulatory networks. We put the field in perspective by first looking at recent developments in the field of bioinformatics, and how these developments contributed to the advance of science. We then describe the approach that is being followed, based on the development of algorithms and information systems for the problems of motif detection, gene expression analysis and inference of gene regulatory networks. We conclude by pointing out possible directions for future research in the fields of systems biology and synthetic biology, two critical areas for the development of science in the coming years.

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References

  1. J. Watson and F. Crick, A structure for Deoxyribose Nucleic Acid, Nature, 171, pp. 737:738, 1953.

    Google Scholar 

  2. R. Staden, A new computer method for the storage and manipulation of DNA gel reading data Nucleic Acids Research, 25;8(16), pp. 3673:94, 1980.

    Google Scholar 

  3. R. A. Gibbs, R.A. Pressing ahead with human genome sequencing. Nature Genetics,. 11, pp. 121:125, 1995.

    Article  Google Scholar 

  4. Commission on Life Sciences, National Research Council. Mapping and Sequencing the Human Genome, National Academy Press: Washington, D.C., 1988.

    Google Scholar 

  5. R. D. Fleischmann, A. D. Adams, O. White, R. A. Clayton, E. F. Kirkness, A. R. Kerlavage, C. J. Bult, J. F. Tomb, B. A. Dougherty, J. M. Merrick et al. Whole-genome random sequencing and assembly of Haemophilus influenzae Rd, Science 269(5223), pp. 496:512, 1995.

    Article  Google Scholar 

  6. Goffeau, B. G. Barrell, H. Bussey, R. W. Davis, B. Dujon, H. Feldmann, F. Gali-bert, J. D. Hoheisel, C. Jacq, M. Johnston, E. J. Louis, H. W. Mewes, Y. Muraka-mi, P. Philippsen, H. Tettelin, S. G. Oliver. Life with 6000 genes. Science. 274(546), pp. 563:567, 1996.

    Google Scholar 

  7. Blattner et al.. The complete genome sequence of Escherichia coli K-12, Science, 277(5331), pp. 1453:1474, 1997.

    Article  Google Scholar 

  8. The C. elegans Sequencing Consortium, Genome Sequence of the Nematode C. elegans: A Platform for Investigating Biology, Science 282(5396), pp. 2012:2018, 1998.

    Google Scholar 

  9. The Arabidopsis Initiative, Analysis of the genome sequence of the flowering plant Arabi-dopsis thaliana, Nature 408, pp. 796:815 2000.

    Google Scholar 

  10. M. Adams et al. Science, The Genome Sequence of Drosophila melanogaster, Science 287(5461), pp. 2185:2195, 2000.

    Article  Google Scholar 

  11. J. C. Venter et al, The Sequence of the Human Genome, Science, 291(5507), pp. 1304:1351, 2001.

    Article  Google Scholar 

  12. International Human Genome Sequencing Consortium, Initial sequencing and analysis of the human genome, Nature 409, pp. 860:921, 2001.

    Google Scholar 

  13. J. L. Weber and E. W. Myers, Human Whole-Genome Shotgun Sequencing, Genome Re-search, 7(5), pp. 401:409, 1997.

    Google Scholar 

  14. S. B. Needleman and C. D. Wunsch, A general method applicable to the search for similarities in the amino acid sequence of two proteins. Journal of Molecular Biology 48, pp. 443:453, 1970.

    Article  Google Scholar 

  15. T. F. Smith and M. S. Waterman, Identification of Common Molecular Subsequences. Journal of Molecular Biology 147, pp. 195:197, 1981.

    Article  Google Scholar 

  16. S. F. Altschul, W. Gish, W. Miller, E. W. Myers, D. J. Lipman, Basic local alignment search tool Journal of Molecular Biology, 215(3):403:10, 1990.

    Google Scholar 

  17. W. R. Pearson and D.J. Lipman. Improved tools for biological sequence comparison. Proceedings of the National Academy of Sciences, 85, pp. 2444:2448, 1988.

    Article  Google Scholar 

  18. E. Uberbacher and R. Mural. Locating protein-coding regions in human DNA sequences by a multiple sensor-neural network approach. Genetics, 88, pp. 11261:11265, 1991.

    Google Scholar 

  19. M. Zhang. Identification of protein coding regions in human genome by quadratic discriminant analysis, Genetics, 94, pp. 565:568, 1997.

    Google Scholar 

  20. C. Burge and S. Karlin. Prediction of complete gene structures in human genomic DNA. Journal of Molecular Biology, 268, pp. 78:94, 1997.

    Article  Google Scholar 

  21. R. Guigó, S. Knudsen, N. Drake and T. F. Smith. Prediction of gene structure. Journal of Molecular Biology, 226, pp. 141:157, 1992.

    Article  Google Scholar 

  22. P. Monteiro, A. Ramalho, A. T. Freitas and A. L. Oliveira, DECIDE A Gene Finding Evaluation Tool, Proceedings of BKDB2005-Bioinformatics: Knowledge Discovery in Biology, pp. 68:72, 2005.

    Google Scholar 

  23. M. Y. Galperin, The Molecular Biology Database Collection: 2006 update Nucleic Acids Research, 34: pp. D3:D5, 2006.

    Article  Google Scholar 

  24. J. M. Cherry, C. Adler, C. A. Ball, S. A. Chervitz, S. S. Dwight, E. T. Hester, Y. Jia, G. Juvik, T. Roe, M. Schroeder, S. Weng and D. Botstein, SGD: Saccharomyces Genome Database. Nucleic Acids Research., 26, pp. 73:79, 1998.

    Article  Google Scholar 

  25. U. Güldener, M. Münsterkötter, G. N. Kastenmüller, J. Strack, C. Lemer, J. Richelles, S. J. Wodak, J. García-Martínez, J. E. Pérez-Ortín, H. Michael, A. Kaps, E. Talla, B. Dujon, B. André, J. L. Souciet, J. D. Montigny, E. Bon, C. Gaillardin and H. W. Mewes CYGD: the comprehensive yeast genome database, Nucleic Acids Research, 33, pp. D364:D368, 2005.

    Google Scholar 

  26. M. Riffle, L. Malmström and T. N. Davis, The yeast resource center public data repository, Nucleic Acids Research, 33, D378–D382, 2005.

    Article  Google Scholar 

  27. J. van Helden, Regulatory sequence analysis tools. Nucleic Acids Research, 31, pp. 3593:3596, 2003.

    Article  Google Scholar 

  28. M. C. Teixeira, P. Monteiro, P. Jain, S. Tenreiro, A. R. Fernandes, N. P. Mira, M. Alenquer, A. T. Freitas, A. L. Oliveira and I. Sá-Correia, The YEASTRACT database: a tool for the analysis of transcription regulatory associations in Saccharomyces cerevisiae, Nucleic Acids Research, 34, pp. D446:D451, 2006.

    Article  Google Scholar 

  29. M. F. Sagot. Spelling approximate repeated or common motifs using a suffix tree, Procee-dings of Latin’98, LNCS 1380, pp. 111:127, 1998.

    Google Scholar 

  30. J. van Helden, A. F. Rios and J. Collado-Vides. Discovering regulatory elements in noncoding sequences by analysis of spaced dyads. Nucleic Acids Research, 28, pp. 1808:1818, 2000.

    Google Scholar 

  31. M. Carvalho, A. T. Freitas, A. L. Oliveira and M. F. Sagot, An efficient algorithm for the identification of structured motifs in DNA promoter sequences, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 3(2), 2006.

    Google Scholar 

  32. M. Carvalho, A. T. Freitas, A. L. Oliveira and M. F. Sagot, A highly scalable algorithm for the extraction of cis-regulatory regions, Proceedings of the 3rd Asia Pacific Bioinformatics Conference, pp. 273:282, 2005.

    Google Scholar 

  33. M. Carvalho, A. T. Freitas, A. L. Oliveira and M. F. Sagot, A parallel algorithm for the extraction of structured motifs, Proceedings of the 19th ACM Symposium on Applied Computing, pp. 147:153, 2004.

    Google Scholar 

  34. J. L. DeRisi, V. R. Iyer, P. O. Brown, Exploring the metabolic and genetic control of gene expression on a genomic scale. Science. 278(5338). pp. 680–686, 1997.

    Article  Google Scholar 

  35. S. le Crom, F. Devaux, C. Jacq, P. Marc, yMGV: helping biologists with yeast microarray data mining, Nucleic Acids Research, 30, pp. 76:9, 2002.

    Article  Google Scholar 

  36. J. E. Celis, M. Kruhøffer, I. Gromova, C. Frederiksen, M. Østergaard, T. Thykjaer, P. Gromov, J. Yu, H. Pálsdóttir, N. Magnusson and T. F. Ørntoft, Gene expression profiling: monitoring transcription and translation products using DNA microarrays and proteo-mics. FEBS Letters 480, pp. 2:16, 2000.

    Article  Google Scholar 

  37. Y. Cheng and G. M. Church, Biclustering of Expression Data, Proceedings of the Eighth International Conference on Intelligent Systems for Molecular Biology, pp. 93:103, 2000.

    Google Scholar 

  38. S. C. Madeira and A. L. Oliveira, Biclustering algorithms for biological data analysis: A survey. IEEE/ACM Transactions on Computational Biology and Bioinformics 1(1), pp. 24:45, 2004.

    Google Scholar 

  39. S. C. Madeira and A. L. Oliveira, A Linear Time Biclustering Algorithm for Time Series Gene Expression Data, Proceedings of the 5th Workshop on Algorithms in Bioinformatics, LNCS 3692, pp. 39:52, 2005.

    Google Scholar 

  40. X. Zhou, X. Wang, R. Pal, I. Ivanov, M. Bittner and E. Dougherty A Bayesian connectivi-ty based approach to constructing probabilistic gene regulatory networks. Bioinformatics, 20 pp. 2918:2927, 2004.

    Google Scholar 

  41. K. Kyoda, K. Baba, S. Onami S and H. Kitano, DBRF-MEGN method: an algorithm for deducing minimum equivalent gene networks from large-scale gene expression profiles of gene deletion mutants, Bioinformatics. 20, pp. 2662:2675, 2004.

    Article  Google Scholar 

  42. T. I. Lee, N. J. Rinaldi, F. Robert, D. T. Odom, Z. Bar-Joseph, G. K. Gerber, N. M. Hannett, C. T. Harbison, C. M. Thompson, I. Simon, J. Zeitlinger, E. G. Jennings, H. L. Murray, D. B. Gordon, B. Ren, J. J. Wyrick, J. B. Tagne, T. L. Volkert, E. Fraenkel, D. K. Gifford and R. A. Young, Transcriptional regulatory networks in Saccharomyces cerevisiae. Science 298, pp. 799:804, 2002.

    Google Scholar 

  43. J. Ihmels, S. Bergmann and N. Barkai, Defining transcription modules using large-scale gene expression data, Bioinformatics, 20, pp. 1993:2003, 2004.

    Article  Google Scholar 

  44. M. Zou and S. D. Conzen, A new dynamic Bayesian network (DBN) approach for identif-ying gene regulatory networks from time course microarray data. Bioinformatics, 21(1), pp. 71:79, 2005.

    Article  Google Scholar 

  45. S. Tenreiro, A. R. Fernandes and I. Sá-Correia Transcriptional activation of FLR1 gene during Saccharomyces cerevisiae adaptation to growth with benomyl: role of Yap1p and Pdr3p. Biochemical and Biophysical Research Communications, 280, pp. 216:222, 2001.

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. IST/INESC-ID, Universidade Técnica de Lisboa, R. Alves Redol, 1000, Lisboa, Portugal

    Arlindo L. Oliveira & Ana T. Freitas

  2. IST/CEBQ, Universidade Técnica de Lisboa, Av. Rovisco Pais, 1000, Lisboa, Portugal

    Isabel Sá-Correia

Authors
  1. Arlindo L. Oliveira
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  2. Ana T. Freitas
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  3. Isabel Sá-Correia
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Editor information

Editors and Affiliations

  1. Technical University of Lisbon, Lisbon, Portugal

    Manuel Seabra Pereira

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Oliveira, A.L., Freitas, A.T., Sá-Correia, I. (2007). Bioinformatics: A New Approach for the Challenges of Molecular Biology. In: Pereira, M.S. (eds) A Portrait of State-of-the-Art Research at the Technical University of Lisbon. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-5690-1_19

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  • DOI: https://doi.org/10.1007/978-1-4020-5690-1_19

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-1-4020-5689-5

  • Online ISBN: 978-1-4020-5690-1

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