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检索条件"丛书名=Advances in Bioinformatics and Computational Biology"

共 63 条记录，以下是31-40 订阅

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Exploring genome rearrangements using virtual hybridization

Exploring genome rearrangements using virtual hybridization

引用

5th Asia-Pacific bioinformatics Conference (APBC2007)

作者： Belcaid, M. Bergeron, A. Chateau, A. Chauve, C. Gingras, Y. Poisson, G. Vendette, M. Univ Hawaii Manoa Informat & Comp Sci Honolulu HI 96822 USA Univ Montreal Comparat Genom Lab Montreal PQ Canada lab Informat Robot & Microelect Montpellier Montpellier France Simon Fraser Univ Dept Math Vancouver BC Canada

ISBN: (纸本)9781860947834

Genomes evolve with both mutations and large scale events, such as inversions, translocations, duplications and losses, that modify the structure of a set of chromosomes. In order to study these types of large-scale events, the first task is to select, in different genomes, sub-sequences that are considered "equivalent'. Many approaches have been used to identify equivalent sequences, either based on biological experiments, gene annotations, or sequence alignments. These techniques suffer from a variety of drawbacks that often result in the impossibility, for independent researchers, to reproduce the datasets used in the studies, or to adapt them to newly sequenced genomes. In this paper, we show that carefully selected small probes can be efficiently used to construct datasets. Once a set of probes is identified - and published -, datasets for whole genome comparisons can be produced, and reproduced, with elementary algorithms;decisions about what is considered an occurrence of a probe in a genome can be criticized and reevaluated;and the structure of a newly sequenced genome can be obtained rapidly, without the need of gene annotations or intensive computations.

关键词： Probes

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Genotype-based case-control analysis, violation of hardy-weinberg equilibrium, and phase diagrams

Genotype-based case-control analysis, violation of hardy-wei...

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5th Asia-Pacific bioinformatics Conference (APBC2007)

作者： Suh, Young Ju Li, Wentian Ewha Womans Univ Coll Med Res Div Med BK21 Seoul South Korea Ewha Womans Univ Coll Med Dept Prevent Med Seoul South Korea North Shore LIJ Hlth Syst Feinstein Inst Med Res Robert S Boas Ctr Genom & Human Genet Manhasset NY 11030 USA

ISBN: (纸本)9781860947834

We study in detail a particular statistical method in genetic case-control analysis, labeled "genotype-based association", in which the two test results from assuming dominant and recessive model are combined in one optimal output. This method differs both from the allele-based association which artificially doubles the sample size, and the direct chi(2) test on 3-by-2 contingency table which may overestimate the degree of freedom. We conclude that the comparative advantage (or disadvantage) of the genotype-based test over the allele-based test mainly depends on two parameters, the allele frequency difference delta and the Hardy-Weinberg disequilibrium coefficient difference delta(epsilon). Six different situations, called "phases", characterized by the two X-2 test statistics in allele-based and genotype-based test, are well separated in the phase diagram parameterized by delta and delta(epsilon). For two major groups of phases, a single parameter theta = tan(-1) (delta/delta(epsilon)) is able to achieves an almost perfect phase separation. We also applied the analytic result to several types of disease models. It is shown that for dominant and additive models, genotype-based tests are favored over allele-based tests.

关键词： Phase diagrams

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Computing the all-pairs quartet distance on a set of evolutionary trees

Computing the all-pairs quartet distance on a set of evoluti...

引用

5th Asia-Pacific bioinformatics Conference (APBC2007)

作者： Stissing, M. Mailund, T. Pedersen, C. N. S. Brodal, G. S. Fagerberg, R. Univ Aarhus Bioinformat Res Ctr Aarhus Denmark Univ Aarhus Dept Comp Sci Aarhus Denmark Univ Southern Denmark Dept Math & Comp Sci Odense Denmark

ISBN: (纸本)9781860947834

We present two algorithms for calculating the quartet distance between all pairs of trees in a set of binary evolutionary trees on a common set of species. The algorithms exploit common substructure among the trees to speed up the pairwise distance calculations thus performing significantly better on large sets of trees compared to performing distinct pairwise distance calculations, as we illustrate experimentally, where we see a speedup factor of around 130 in the best case.

关键词： Binary trees

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Combining N-grams and alignment in G-protein coupling specificity prediction

Combining N-grams and alignment in G-protein coupling specif...

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5th Asia-Pacific bioinformatics Conference (APBC2007)

作者： Cheng, Betty Yee Man Carbonell, Jaime G. Carnegie Mellon Univ Sch Comp Sci Language Technol Inst 5000 Forbes Ave Pittsburgh PA 15213 USA

ISBN: (纸本)9781860947834

G-protein coupled receptors (GPCR) interact with G-proteins to regulate much of the cell's response to external stimuli;abnormalities in which cause numerous diseases. We developed a new method to predict the families of G-proteins with which it interacts, given its residue sequence. We combine both alignment and n-gram features. The former captures long-range interactions but assumes the linear ordering of conserved segments is preserved. The latter makes no such assumption but cannot capture long-range interactions. By combining alignment and n-gram features, and using the entire GPCR sequence (instead of intracellular regions alone, as was done by others), our method outperformed the current state-of-the-art in precision, recall and F1, attaining 0.753 in F1 and 0.796 in accuracy on the PTbase 2004 dataset. Moreover, analysis of our results shows that the majority of coupling specificity information lies in the beginning of the 2nd intracellular loop and over the length of the 3rd.

关键词： Proteins

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An efficient biclustering algorithm for finding genes with similar patterns in time-series expression data

An efficient biclustering algorithm for finding genes with s...

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5th Asia-Pacific bioinformatics Conference (APBC2007)

作者： Madeira, Sara C. Oliveira, Arlindo L. Univ Beira Interior INESC ID IST Rua Marques Avila & Boloma P-6200001 Covilha Portugal INESC ID IST P-1000039 Lisbon Portugal

ISBN: (纸本)9781860947834

Biclustering algorithms have emerged as an important tool for the discovery of local patterns in gene expression data. For the case where the expression data corresponds to time-series, efficient algorithms that work with a discretized version of the expression matrix are known. However, these algorithms assume that the biclusters to be found are perfect, in the sense that each gene in the bicluster exhibits exactly the same expression pattern along the conditions that belong to it. In this work, we propose an algorithm that identifies genes with similar, but not necessarily equal, expression patterns, over a subset of the conditions. The results demonstrate that this approach identifies biclusters biologically more significant than those discovered by other algorithms in the literature.

关键词： Time series

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Using formal concept analysis for microarray data comparison

Using formal concept analysis for microarray data comparison

引用

5th Asia-Pacific bioinformatics Conference (APBC2007)

作者： Choi, V. Huang, Y. Lam, V. Potter, D. Laubenbacher, R. Duca, K. Virginia Tech Dept Comp Sci 660 McBryde Hall Blacksburg VA 24061 USA Rutgers State Univ Dept Comp Sci Piscataway NJ 08854 USA Virginia Tech Virginia Bioinformat Inst Blacksburg VA 24061 USA

ISBN: (纸本)9781860947834

Microarray technologies, which can measure tens of thousands of gene expression values simultaneously in a single experiment, have become a common research method for biomedical researchers. computational tools to analyze microarray data for biological discovery are needed. In this paper, we investigate the feasibility of using Formal Concept Analysis (FCA) as a tool for microarray data analysis. The method of FCA builds a (concept) lattice from the experimental data together with additional biological information. For microarray data, each vertex of the lattice corresponds to a subset of genes that are grouped together according to their expression values and some biological information related to gene function. The lattice structure of these gene sets might reflect biological relationships in the dataset. Similarities and differences between experiments can then be investigated by comparing their corresponding lattices according to various graph measures. We apply our method to microarray data derived from influenza infected mouse lung tissue and healthy controls. Our preliminary results show the promise of our method as a tool for microarray data analysis.

关键词： Formal concept analysis

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Selecting genes with dissimilar discrimination strength for sample class prediction

Selecting genes with dissimilar discrimination strength for ...

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5th Asia-Pacific bioinformatics Conference (APBC2007)

作者： Cai, Zhipeng Goebel, Randy Salavatipour, Mohammad R. Shi, Yi Xu, Lizhe Lin, Guohiji Univ Alberta Dept Comp Sci Edmonton AB T6G 2E8 Canada

ISBN: (纸本)9781860947834

One of the main applications of microarray technology is to determine the gene expression profiles of diseases and disease treatments. This is typically done by selecting a small number of genes from amongst thousands to tens of thousands, whose expression values are collectively used as classification profiles. This gene selection process is notoriously challenging because microarray data normally contains only a very small number of samples, but range over thousands to tens of thousands of genes. Most existing gene selection methods carefully define a function to score the differential levels of gene expression under a variety of conditions, in order to identify top-ranked genes. Such single gene scoring methods suffer because some selected genes have very similar expression patterns so using them all in classification is largely redundant. Furthermore, these selected genes can prevent the consideration of other individually-less but collectively-more differentially expressed genes. We propose to cluster genes in terms of their class discrimination strength and to limit the number of selected genes per cluster. By combining this idea with several existing single gene scoring methods, we show by experiments on two cancer microarray datasets that our methods identify gene subsets which collectively have significantly higher classification accuracies.

关键词： Diseases

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De novo peptide sequencing for mass spectra based on multi-charge strong tags

De novo peptide sequencing for mass spectra based on multi-c...

引用

5th Asia-Pacific bioinformatics Conference (APBC2007)

作者： Ning, Kang Chong, Ket Fah Leong, Hon Wai Natl Univ Singapore Dept Comp Sci 3 Sci Dr 2 Singapore 117543 Singapore

ISBN: (纸本)9781860947834

This paper presents an improved algorithm for de trove, sequencing of multi-charge mass spectra. Recent work based on the analysis of multi-charge mass spectra showed that taking advantage of multi-charge information can lead to higher accuracy (sensitivity and specificity) in peptide sequencing. A simple de novo algorithm, called GBST (Greedy algorithm with Best Strong Tag) was proposed and was shown to produce good results for spectra with charge > 2. In this paper, we analyze some of the shortcomings of GBST. We then present a new algorithm GST-SPC, by extending the GBST algorithm in two directions. First, we use a larger set of multi-charge strong tags and show that this improves the theoretical upper bound on performance. Second, we give an algorithm that computes a peptide sequence that is optimal with respect to shared peaks count from among all sequences that are derived from multi-charge strong tags. Experimental results demonstrate the improvement of GST-SPC over GBST.

关键词： Peptides

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Deriving protein structure topology from the helix skeleton in low resolution density map using rosetta

Deriving protein structure topology from the helix skeleton ...

引用

5th Asia-Pacific bioinformatics Conference (APBC2007)

作者： Lu, Yonggang He, Jing Strauss, Charlie E. M. New Mexico State Univ Dept Comp Sci Las Cruces NM 88003 USA Los Alamos Natl Lab Biosci Div Los Alamos NM 87545 USA

ISBN: (纸本)9781860947834

Electron cryo-microscopy (cryo-EM) is an experimental technique to determine the 3-dimensional structure for large protein complexes. Currently this technique is able to generate protein density maps at 6 to 9 angstrom resolution. Although secondary structures such as a-helix and P-sheet can be visualized from these maps, there is no mature approach to deduce their tertiary topology, the linear order of the secondary structures on the sequence. The problem is challenging because given N secondary structure elements, the number of possible orders is (2(N))*N!. We have developed a method to predict the topology of the secondary structures using ab initio structure prediction. The Rosetta structure prediction algorithm was used to make purely sequence based structure predictions for the protein. We produced 1000 of these ab initio models, and then screened the models produced by Rosetta for agreement with the helix skeleton derived from the density map. The method was benchmarked on 60 mainly alpha helical proteins, finding that for about 3/4 of all the proteins, the majority of the helices in the skeleton were correctly assigned by one of the top 10 suggested topologies from the method, while for about 1/3 of all the proteins the best topology assignment without errors was ranked the first. This approach also provides an estimate of the sequence alignment of the skeleton. For most of those true-positive assignments, the alignment was accurate to within +/- 2 amino acids in the sequence.

关键词： Topology

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computational Systems bioinformatics

引用

丛书名： Series on advances in bioinformatics and computational biology

2007年

作者： Peter Markstein Ying Xu

ISBN: (数字)9781860948732

ISBN: (纸本)9781860948725

This volume contains about 40 papers covering many of the latest developments in the fast-growing field of bioinformatics. The contributions span a wide range of topics, including computational genomics and genetics, protein function and computational proteomics, the transcriptome, structural bioinformatics, microarray data analysis, motif identification, biological pathways and systems, and biomedical applications. Abstracts from the keynote addresses and invited talks are also *** papers not only cover theoretical aspects of bioinformatics but also delve into the application of new methods, with input from computation, engineering and biology disciplines. This multidisciplinary approach to bioinformatics gives these proceedings a unique viewpoint of the field.

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