Transactions on Computational Systems Biology II

Alexander Zelikovsky
Springer Science & Business Media, 04.11.2005 - 156 Seiten
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It gives me great pleasure to present the Special Issue of LNCS Transactions on Computational Systems Biology devoted to considerably extended versions of selected papers presented at the International Workshop on Bioinformatics Research and Applications (IWBRA 2005). The IWBRA workshop was a part of the International Conference on Computational Science (ICCS 2005) which took place in Emory University, Atlanta, Georgia, USA, May 22–24, 2005. See iwbra.htm for more details. The 10 papers selected for the special issue cover a wide range of bioinformatics research. The first papers are devoted to problems in RNA structure prediction: Blin et al. contribute to the arc-preserving subsequence problem and Liu et al. develop an efficient search of pseudoknots. The coding schemes and structural alphabets for protein structure prediction are discussed in the contributions of Lei and Dai, and Zheng and Liu, respectively. Song et al. propose a novel technique for efficient extraction of biomedical information. Nakhleh and Wang discuss introducing hybrid speciation and horizontal gene transfer in phylogenetic networks. Practical algorithms minimizing recombinations in pedigree phasing are proposed by Zhang et al. Kolliet al. propose a new parallel implementation in OpenMP for finding the edit distance between two signed gene permutations. The issue is concluded with two papers devoted to bioinformatics problems that arise in DNA microarrays: improved tag set design for universal tag arrays is suggested by Mandoiu et al. and a new method of gene selection is discussed by Xu and Zhang.

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What Makes the ArcPreserving Subsequence Problem Hard?
Profiling and Searching for RNA Pseudoknot Structures in Genomes
A Protein Structural Alphabet and Its Substitution Matrix CLESUM
Properties and Relationship to Trees
Minimum ParentOffspring Recombination Haplotype Inference
Calculating Genomic Distances in Parallel Using OpenMP
Using Correlations Between Genes to Select Informative
Author Index

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