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2005 IEEE Computational Systems Bioinformatics Conference (CSB'05)

Date 8-11 Aug. 2005

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Displaying Results 1 - 25 of 53
  • 2005 IEEE Computational Systems Bioinformatics Conference - Cover

    Publication Year: 2005, Page(s): c1
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  • Proceedings. 2005 IEEE Computational Systems Bioinformatics Conference

    Publication Year: 2005
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  • 2005 IEEE Computational Systems Bioinformatics Conference - Copyright Page

    Publication Year: 2005, Page(s): iv
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  • 2005 IEEE Computational Systems Bioinformatics Conference - Table of contents

    Publication Year: 2005, Page(s):v - viii
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  • Preface

    Publication Year: 2005, Page(s): ix
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  • Committees

    Publication Year: 2005, Page(s):x - xi
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  • Referees

    Publication Year: 2005, Page(s):xii - xiii
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  • Challenges in Creating an Infrastructure for Physics-Based Simulation of Biological Structures

    Publication Year: 2005, Page(s): 3
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  • Ontologies for Biologists - A Community Model for the Annotation of Genomic Data

    Publication Year: 2005, Page(s): 7
    Cited by:  Papers (1)
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  • The National Alliance for Medical Imaging Computing (NA-MIC)

    Publication Year: 2005, Page(s): 8
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  • The Center for Computational Biology

    Publication Year: 2005, Page(s): 9
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  • Identifying simple discriminatory gene vectors with an information theory approach

    Publication Year: 2005, Page(s):13 - 24
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (224 KB) | HTML iconHTML

    In the feature selection of cancer classification problems, many existing methods consider genes individually by choosing the top genes which have the most significant signal-to-noise statistic or correlation coefficient. However the information of the class distinction provided by such genes may overlap intensively, since their gene expression patterns are similar The redundancy of including many... View full abstract»

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  • Learning yeast gene functions from heterogeneous sources of data using hybrid weighted Bayesian networks

    Publication Year: 2005, Page(s):25 - 34
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (304 KB) | HTML iconHTML

    We developed a machine learning system for determining gene functions from heterogeneous sources of data sets using a Weighted Naive Bayesian Network (WNB). The knowledge of gene functions is crucial for understanding many fundamental biological mechanisms such as regulatory pathways, cell cycles and diseases. Our major goal is to accurately infer functions of putative genes or ORFs (Open Reading ... View full abstract»

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  • Consensus genetic maps: a graph theoretic approach

    Publication Year: 2005, Page(s):35 - 43
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (400 KB) | HTML iconHTML

    A genetic map is an ordering of genetic markers constructed from genetic linkage data for use in linkage studies and experimental design. While traditional methods have focused on constructing maps from a single population study, increasingly maps are generated for multiple lines and populations of the same organism. For example, in crop plants, where the genetic variability is high, researchers h... View full abstract»

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  • Gene teams with relaxed proximity constraint

    Publication Year: 2005, Page(s):44 - 55
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1144 KB) | HTML iconHTML

    Functionally related genes co-evolve, probably due to the strong selection pressure in evolution. Thus we expect that they are present in multiple genomes. Physical proximity among genes, known as gene team, is a very useful concept to discover functionally related genes in multiple genomes. However there are also many gene sets that do not preserve physical proximity. In this paper, we generalize... View full abstract»

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  • Efficient algorithms and software for detection of full-length LTR retrotransposons

    Publication Year: 2005, Page(s):56 - 64
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (264 KB) | HTML iconHTML

    LTR retrotransposons constitute one of the most abundant classes of repetitive elements in eukaryotic genomes. In this paper, we present a new algorithm for detection of full-length LTR retrotransposons in genomic sequences. The algorithm identifies regions in a genomic sequence that show structural characteristics of LTR retrotransposons. Three key components distinguish our algorithm from that o... View full abstract»

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  • Islands of tractability for parsimony haplotyping

    Publication Year: 2005, Page(s):65 - 72
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (168 KB) | HTML iconHTML

    We study the parsimony approach to haplotype inference, which calls for finding a set ofhaplotypes of minimum cardinality that explains an input set of genotypes. We prove that the problem is APX-hard even in very restricted cases. On the positive side, we identify islands of tractability for the problem, by focusing on instances with specific structure of haplotype sharing among the input genotyp... View full abstract»

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  • Accurate prediction of orthologous gene groups in microbes

    Publication Year: 2005, Page(s):73 - 79
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (312 KB) | HTML iconHTML

    We present a new computational method for the prediction of orthologous gene groups for microbial genomes based on the prediction of co-occurrences of homologous genes. The method is inspired by the observation that homologous genes are highly likely to be orthologous if their neighboring genes are also homologous. Based on co-occurrences of homologous genes, we have grouped the (predicted) operon... View full abstract»

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  • Motif extraction and protein classification

    Publication Year: 2005, Page(s):80 - 85
    Cited by:  Papers (2)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (160 KB) | HTML iconHTML

    We present a novel unsupervised method for extracting meaningful motifs from biological sequence data. This de novo motif extraction (MEX) algorithm is data driven, finding motifs that are not necessarily over-represented in the data. Applying MEX to the oxidoreductases class of enzymes, containing approximately 7000 enzyme sequences, a relatively small set of motifs is obtained. This set spans a ... View full abstract»

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  • Discriminative discovery of transcription factor binding sites from location data

    Publication Year: 2005, Page(s):86 - 89
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (296 KB) | HTML iconHTML

    The availability of genome-wide location analyses based on chromatin immunoprecipitation (CMP) data gives a new insight for in silico analysis of transcriptional regulations. We propose a novel discriminative discovery framework for precisely identifying transcriptional regulatory motifs from both positive and negative samples (sets of upstream sequences of both bound and unbound genes by a transc... View full abstract»

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  • Reconstructing phylogenetic networks using maximum parsimony

    Publication Year: 2005, Page(s):93 - 102
    Cited by:  Papers (8)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (176 KB) | HTML iconHTML

    Phylogenies-the evolutionary histories of groups of organisms-are one of the most widely used tools throughout the life sciences, as well as objects of research within systematics, evolutionary biology, epidemiology, etc. Almost every tool devised to date to reconstruct phylogenies produces trees; yet it is widely understood and accepted that trees oversimplify the evolutionary histories of many g... View full abstract»

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  • An efficient algorithm for perfect phylogeny haplotyping

    Publication Year: 2005, Page(s):103 - 110
    Cited by:  Papers (1)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (184 KB) | HTML iconHTML

    The Perfect Phylogeny Haplotyping (PPH) problem is one of the many computational approaches to the Haplotype Inference (HI) problem. Though there are many O(nm2) solutions to the PPH problem, the complexity of the PPH problem itself has remained an open question. In this paper, we introduce the FlexTree data structure that represents all the solutions for a PPH instance. We also introdu... View full abstract»

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  • TreeRefiner: a tool for refining a multiple alignment on a phylogenetic tree

    Publication Year: 2005, Page(s):111 - 119
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (272 KB) | HTML iconHTML

    We present TreeRefiner, a tool for refining multiple alignments of biological sequences. Given a multiple alignment, a phylogenetic tree, and scoring parameters as input, TreeRefiner optimizes the sum-of-pairs function in a restricted three-dimensional space around the alignment. At each internal node of the unrooted tree, the multiple alignment is projected to the sub-alignments corresponding to ... View full abstract»

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  • Multi-metric and multi-substructure biclustering analysis for gene expression data

    Publication Year: 2005, Page(s):123 - 134
    Cited by:  Papers (4)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (336 KB) | HTML iconHTML

    A good number of biclustering algorithms have been proposed for grouping gene expression data. Many of them have adopted matrix norms to define the similarity score of a bicluster. We shall show that almost all matrix metrics can be converted into vector norms while presenting the rank equivalence. Vector norms provide a much more efficient vehicle for biclustering analysis and computation. The ad... View full abstract»

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  • Analysis of SNP-expression association matrices

    Publication Year: 2005, Page(s):135 - 143
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (216 KB) | HTML iconHTML

    High throughput expression profiling and genotyping technologies provide the means to study the genetic determinants of population variation in gene expression variation. In this paper we present a general statistical framework for the simultaneous analysis of gene expression data and SNP genotype data measured for the same cohort. The framework consists of methods to associate transcripts with SN... View full abstract»

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