2008 International Conference on BioMedical Engineering and Informatics

27-30 May 2008

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  • [Front cover - Vol 1]

    Publication Year: 2008, Page(s): C1
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  • [Title page i - Volume 1]

    Publication Year: 2008, Page(s): i
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  • [Title page iii - Volume 1]

    Publication Year: 2008, Page(s): iii
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  • [Copyright notice - Volume 1]

    Publication Year: 2008, Page(s): iv
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  • Table of contents - Volume 1

    Publication Year: 2008, Page(s):v - xvi
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  • Preface - Volume 1

    Publication Year: 2008, Page(s): xvii
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  • Organizing Committee - Volume 1

    Publication Year: 2008, Page(s): xviii
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  • Program Committee - Volume 1

    Publication Year: 2008, Page(s):xix - xx
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  • list-reviewer

    Publication Year: 2008, Page(s):xxi - xxii
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  • A Fast Agglomerate Algorithm for Mining Functional Modules in Protein Interaction Networks

    Publication Year: 2008, Page(s):3 - 7
    Cited by:  Papers (15)
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (308 KB) | HTML iconHTML

    As advanced in the technologies of predicting protein-protein interactions, huge data sets portrayed as networks have been generated. Identification of functional modules from such networks is crucial for understanding principles of cellular organization and functions. In this paper, we presented a new fast agglomerate algorithm of identifying functional modules based on the edge clustering coeffi... View full abstract»

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  • A Fast Exact Pattern Matching Algorithm for Biological Sequences

    Publication Year: 2008, Page(s):8 - 12
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (333 KB) | HTML iconHTML

    Pattern matching is a powerful tool for querying sequence patterns in the biological sequence databases. The remarkable increase in the number of DNA and proteins sequences has also stimulated the study of many pattern matching algorithms. To further raise the performance of the pattern matching algorithm, a fast exact algorithm (called BRFS) is presented. It bases on the method of FS algorithm an... View full abstract»

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  • A Greedy Two-stage Gibbs Sampling Method for Motif Discovery in Biological Sequences

    Publication Year: 2008, Page(s):13 - 17
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (330 KB) | HTML iconHTML

    For the motif discovery problem of DNA sequences, a greedy two-stage Gibbs sampling algorithm is presented, and the related software package is called Greedy MotifSAM. Based on position weight matrix (PWM) motif model, a greedy strategy for choosing the initial parameters of PWM is employed. Two sampling methods, site sampler and motif sampler, are used. Site sampler is used to find one occurrence... View full abstract»

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  • A Multiple Regression Approach for Building Genetic Networks

    Publication Year: 2008, Page(s):18 - 23
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (506 KB) | HTML iconHTML

    The construction of genetic regulatory networks from time series gene expression data is an important research topic in bioinformatics as large amounts of quantitative gene expression data can be routinely generated nowadays. One of the main difficulties in building such genetic networks is that the data set has huge number of genes but small number of time points. In this paper, we propose a line... View full abstract»

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  • A Novel Analysis Model for DNA Sequences

    Publication Year: 2008, Page(s):24 - 28
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (275 KB) | HTML iconHTML

    A novel analysis model for DNA sequence based on Stephen S.-T. Yau's method is presented. The model adopts a trigonometric function to represent the four nucleotides A, G, C, and T in a DNA sequence, and has some interesting characteristics. Basing on the characteristics, statistical experiments on human gene coding regions show high possibility of significant peak at the frequency k = N/3 in thei... View full abstract»

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  • A New Approach Combined Fuzzy Clustering and Bayesian Networks for Modeling Gene Regulatory Networks

    Publication Year: 2008, Page(s):29 - 33
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (157 KB) | HTML iconHTML

    The appearance of microarray technologies makes it possible to simultaneously monitor the expression levels for tens of thousands of genes. Bayesian Network (BN) is an important approach for predicting gene regulatory networks from expression data. However, two fundamental problems greatly reduce the effectiveness of current BN methods. The first problem is much less samples than genes, it makes t... View full abstract»

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  • A New Approach for Tree Alignment Based on Local Re-Optimization

    Publication Year: 2008, Page(s):34 - 38
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (263 KB) | HTML iconHTML

    Multiple sequence alignment is the most fundamental task in bioinformatics and computational biology. In this paper, we present a new algorithm to conduct multiple sequences alignment based on phylogenetic trees. It is widely accepted that a good phylogenetic tree can help produce high quality alignment, but the direct dynamic programming solution grows exponentially [13]. To overcome this problem... View full abstract»

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  • A New DNA Fragment Assembly Method Based on Long Fragment Filtration

    Publication Year: 2008, Page(s):39 - 46
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (347 KB) | HTML iconHTML

    As an important aspect of bioinformatics, the main problem of genome sequencing is DNA Fragment Assembly. This paper proposed a new fragment assembly algorithm based on the long fragment filtration. Firstly, the fragment set was divided into two parts according to a threshold of the filtration length and the Bruijn graph was formed by the short fragments set. Subsequently system automatically sele... View full abstract»

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  • A Note on the Fast BRAIN Learning Algorithm

    Publication Year: 2008, Page(s):47 - 51
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (341 KB) | HTML iconHTML

    In this paper, an underlying problem on the fast BRAIN learning algorithm is pointed out, which is avoided by introducing the quantity count (middot, middot). In addition, its speed advantage can still be enjoyed only at a cost of a little additional space. The improved fast BRAIN learning algorithm is also given, and the experiments on NN269 dataset validate our analysis. View full abstract»

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  • An Efficient Method for Sampling and Computing Molecular Surface

    Publication Year: 2008, Page(s):52 - 56
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (621 KB) | HTML iconHTML

    An atom-centered protocol based method for surface sampling in grid space is proposed. Van der Waals, solvent-accessible and solvent-excluded surface can be generated in a unified framework. A spherical hash function is used to mark whether the points are inside a sphere, and the hash tables are used to record which spheres the surface points locate on. The proposed method can be modified to apply... View full abstract»

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  • An Improved Longest Common Subsequence Algorithm for Reducing Memory Complexity in Global Alignment of DNA Sequences

    Publication Year: 2008, Page(s):57 - 61
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (323 KB) | HTML iconHTML

    The comparison of biological sequences is one of the oldest problems in computational biology. Global alignment is designed to search for highly similar regions in two DNA sequences, where appear in the same order and orientation. Longest Common Subsequence (LCS) is the most typical algorithm for global alignment that has optimal solution and independent to the shape of its input sequences. Since ... View full abstract»

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  • An Improved Method Based on Maximal Clique for Predicting Interactions in Protein Interaction Networks

    Publication Year: 2008, Page(s):62 - 66
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (314 KB) | HTML iconHTML

    The datasets identified by large-scale, high- throughput methods typically suffer from a relatively high level of noise. Combining the distribution characteristics of noise data and topological properties in the protein interaction network, we described a novel method to improve the reliability of those datasets by predicting missed interactions. The main idea of the method is to predict the inter... View full abstract»

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  • An Ion Transformation Approach for De Novo Peptide Sequencing via Tandem Mass Spectra

    Publication Year: 2008, Page(s):67 - 71
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (308 KB) | HTML iconHTML

    De novo peptide sequencing is especially useful in the identification of unknown proteins. A class of efficient models on de novo peptide interpretation have been proposed recently based on graph theory. However, majority of the graph-based models convert each peak to multiple nodes in the graph due to unknown ion types. This directly results in the decrease of the efficiency and accuracy of pepti... View full abstract»

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  • A Practical Exact Algorithm for the Individual Haplotyping Problem MEC

    Publication Year: 2008, Page(s):72 - 76
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (332 KB) | HTML iconHTML

    The individual haplotyping problem MEC is a computational problem that, given a set of DNA sequence fragment data of an individual, induces the corresponding haplotypes by changing the smallest number of SNPs. MEC problem is NP-hard and there has been no practical exact algorithm to solve the problem. In DNA sequencing experiments, due to technical limits, the maximum length of a fragment sequence... View full abstract»

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  • Analysis and Prediction of Global and Subfamily-specific Functional Sites in Bioaminergic Receptors

    Publication Year: 2008, Page(s):77 - 82
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (498 KB) | HTML iconHTML

    Bioaminergic receptors are involved in controlling a variety of physiological functions. An approach to predict the functional sites in bioaminergic receptors was described and applied in this study. Given an alignment and receptors with already known subfamily definition, the method identified the global and subfamily-specific functional sites based on the position-specific conservation score in ... View full abstract»

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  • Application of Improved K-mean Clustering in Predicting Protein-Protein Interactions

    Publication Year: 2008, Page(s):83 - 86
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (303 KB) | HTML iconHTML

    With the increasing availability of complete genome sequences, there are more excellent opportunity for further research and development of tools for functional studies in proteomics. Phylogenetic profile is a basic non-homology method in functional proteomics. This paper describes the theory of phylogenetic profile, focuses on the improvement of K-mean clustering algorithm in analyzing the protei... View full abstract»

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