Computational Life Sciences II: Second International by Michael Hirsch, Allan Tucker, Stephen Swift, Nigel Martin,

By Michael Hirsch, Allan Tucker, Stephen Swift, Nigel Martin, Christine Orengo (auth.), Michael R. Berthold, Robert C. Glen, Ingrid Fischer (eds.)

This publication constitutes the refereed complaints of the second one foreign Symposium on Computational lifestyles Sciences, CompLife 2006, held in Cambridge, united kingdom, in September 2006.

The 25 revised complete papers offered have been conscientiously reviewed and chosen from fifty six preliminary submissions. The papers are prepared in topical sections on genomics, information mining, molecular simulation, molecular informatics, structures biology, organic networks/metabolism, and computational neuroscience.

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However, it can only find short repeats with length O(log N ). The main use of their algorithm is therefore for extracting short motifs only. Instead of finding short approximate repeats of sequences as mentioned above, our paper finds the long conserved regions with relatively large edit-distance between multiple input sequences (genes). Moreover, our algorithm outputs only “significant” approximate repeats for diminishing the size of output such that the later analysis of the long conserved regions can be more efficient.

637-649. hk 6 School of Electronic and Information Engineering, University of Sydney, NSW2006, Australia Abstract. Spectral analysis of DNA microarray gene expressions time series data is important for understanding the regulation of gene expression and gene function of the Plasmodium falciparum in the intraerythrocytic developmental cycle. In this paper, we propose a new strategy to analyze the cell cycle regulation of gene expression profiles based on the combination of singular spectrum analysis (SSA) and autoregressive (AR) spectral estimation.

References 1. Fickett, J. , and A. G. Hatzigeorgiou, 1997, Eukaryotic Promoter Recognition: Genome Research, v. 7, p. 861-878. 2. Bajic, V. , S. L. Tan, Y. Suzuki, and S. Sugano, 2004, Promoter prediction analysis on the whole human genome: Nature Biotechnology, v. 22, p. 1467 - 1473. 3. Pedersen, A. , P. Baldi, Y. Chauvin, and S. Brunak, 1998, DNA Structure in Human RNA Polymerase II Promoters: J. Mol. , v. 281, p. 663-673. 4. , Y. Saeys, S. Degroeve, P. Rouze, and Y. Van de Peer, 2005, Large-scale structural analysis of the core promoter in mammalian and plant genomes: Nucl.

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