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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11-20 订阅

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A randomized algorithm for comparing sets of phylogenetic trees

A randomized algorithm for comparing sets of phylogenetic tr...

引用

5th Asia-Pacific bioinformatics Conference (APBC2007)

作者： Sul, Seung-Jin Williams, Tiffani L. Texas A&M Univ Dept Comp Sci College Stn TX 77843 USA

ISBN: (纸本)9781860947834

Phylogenetic analysis often produce a large number of candidate evolutionary trees, each a hypothesis of the "true" tree. Post-processing techniques such as strict consensus trees are widely used to summarize the evolutionary relationships into a single tree. However, valuable information is lost during the summarization process. A more elementary step is to produce estimates of the topological differences that exist among all pairs of trees. We design a new randomized algorithm, called Hash-RF, that computes the all-to-all Robinson-Foulds (RF) distance-the most common distance metric for comparing two phylogenetic trees. Our approach uses a hash table to organize the bipartitions of a tree, and a universal hashing function makes our algorithm randomized. We compare the performance of our Hash-RF algorithm to PAUP*'s implementation of computing the all-to-all RF distance matrix. Our experiments focus on the algorithmic performance of comparing sets of biological trees, where the size of each tree ranged from 500 to 2,000 taxa and the collection of trees varied from 200 to 1,000 trees. Our experimental results clearly show that our Hash-RF algorithm is up to 500 times faster than PAUP*'s approach. Thus, Hash-RF provides an efficient alternative to a single tree summary of a collection of trees and potentially gives researchers the ability to explore their data in new and interesting ways.

关键词： Trees (mathematics)

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A novel clustering method for analysis of biological networks using maximal components of graphs

A novel clustering method for analysis of biological network...

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5th Asia-Pacific bioinformatics Conference (APBC2007)

作者： Hayashida, Morihiro Akutsu, Tatsuya Nagamochi, Hiroshi Kyoto Univ Inst Chem Res Bioinformat Ctr Uji Kyoto 6110011 Japan Kyoto Univ Grad Sch Informat Dept Appl Math & Phys Kyoto Kyoto 6068501 Japan

ISBN: (纸本)9781860947834

This paper proposes a novel clustering method for analyzing biological networks. In this method, each biological network is treated as an undirected graph and edges are weighted based on similarities of nodes. Then, maximal components, which are defined based on edge connectivity, are computed and the nodes are partitioned into clusters by selecting disjoint maximal components. The proposed method was applied to clustering of protein sequences and was compared with conventional clustering methods. The obtained clusters were evaluated using P-values for GO (GeneOntology) terms. The average P-values for the proposed method were better than those for other methods.

关键词： Cluster analysis

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Inferring a chemical structure from a feature vector based on frequency of labeled paths and small fragments

Inferring a chemical structure from a feature vector based o...

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5th Asia-Pacific bioinformatics Conference (APBC2007)

作者： Akutsu, Tatsuya Fukagawa, Daiji Kyoto Univ Bioinformat Ctr Chem Res Inst Uji Kyoto 6110011 Japan Natl Inst Informat Chiyoda Ku Tokyo 1018430 Japan

ISBN: (纸本)9781860947834

This paper proposes algorithms for inferring a chemical structure from a feature vector based on frequency of labeled paths and small fragments, where this inference problem has a potential application to drug design, In this paper, chemical structures are modeled as trees or tree-like structures. It is shown that the inference problems for these kinds of structures can be solved in polynomial time using dynamic programming-based algorithms. Since these algorithms are not practical, a branch-and-bound type algorithm is also proposed. The result of computational experiment suggests that the algorithm can solve the inference problem in a few or few-tens of seconds for moderate size chemical compounds.

关键词： Structure (composition)

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Fast structural similarity search based on topology string matching

Fast structural similarity search based on topology string m...

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5th Asia-Pacific bioinformatics Conference (APBC2007)

作者： Park, Sung-Hee Gilbert, David Ryu, Keun Ho Univ Glasgow Dept Comp Sci Bioinformat Res Ctr Glasgow G12 8QQ Lanark Scotland Chungbuk Natl Univ Cheongju 361763 South Korea

ISBN: (纸本)9781860947834

We describe an abstract data model of protein structures by representing the geometry of proteins using spatial data types and present a framework for fast structural similarity search based on the matching of topology strings using bipartite graph matching. The system has been implemented on top of the Oracle 9i spatial database management system. The performance evaluation was conducted on 36 proteins from the Chew and Kedem data set and also on a subset of the PDB40. Our method per-forms well in terms of the quality of matching whilst having the advantage of fast execution and being able to compute similarity search in polynomial time. Thus, this work shows that the pre-computed string representation of topological properties between secondary structure elements using spatial relationships of spatial database management system is practical for fast structural similarity search.

关键词： Topology

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Algorithmic approaches to selecting control clones in dna array hybridization experiments

Algorithmic approaches to selecting control clones in dna ar...

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5th Asia-Pacific bioinformatics Conference (APBC2007)

作者： Fu, Q. Bent, E. Borneman, J. Chrobak, M. Young, N. Univ Calif Riverside Dept Comp Sci Riverside CA 92521 USA Univ Calif Riverside Dept Plant Pathol Riverside CA 92521 USA

ISBN: (纸本)9781860947834

We study the problem of selecting control clones in DNA array hybridization experiments. The problem arises in the OFRG method for analyzing microbial communities. The OFRG method performs classification of rRNA gene clones using binary fingerprints created from a series of hybridization experiments, where each experiment consists of hybridizing a collection of arrayed clones with a single oligonucleotide probe. This experiment produces analog signals, one for each clone, which then need to be classified, that is, converted into binary values 1 and 0 that represent hybridization and non-hybridization events. Besides the sample clones, the array contains a number of control clones needed to calibrate the classification procedure of the hybridization signals. These control clones must be selected with care to optimize the classification process. We formulate this as a combinatorial optimization problem called Balanced Covering. We prove that the problem is NP-hard and we show some results on hardness of approximation. We propose an approximation algorithm based on randomized rounding and we show that, with high probability, it approximates well the optimum. The experimental results confirm that the algorithm finds high quality control clones. The algorithm has been implemented and is publicly available as part of the software package called CloneTools.

关键词： Approximation algorithms

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All hits all the time: Parameter free calculation of seed sensitivity

All hits all the time: Parameter free calculation of seed se...

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5th Asia-Pacific bioinformatics Conference (APBC2007)

作者： Mak, Denise Y. F. Benson, Gary Boston Univ Grad Program Bioinformat Boston MA 02215 USA Boston Univ Dept Biol Dept Comp Sci Boston MA 02215 USA

ISBN: (纸本)9781860947834

Standard search techniques for DNA repeats start by identifying seeds, that is, small matching words, that may inhabit larger repeats. Recent innovations in seed structure have led to the development of spaced seeds [8] and indel seeds [9] which are more sensitive than contiguous seeds (also known as k-mers, k-tuples, l-words, etc.). Evaluating seed sensitivity requires 1) specifying a homology model which describes types of alignments that can occur between two copies of a repeat, and 2) assigning probabilities to those alignments. Optimal seed selection is a resource intensive activity because essentially all alternative seeds must be tested [7]. Current methods require that the model and probability parameters be specified in advance. When the parameters change, the entire calculation has to be rerun. In this paper, we show how to eliminate the need for prior parameter specification. The ideas presented follow from a simple observation: given a homology model, the alignments hit by a particular seed remain the same regardless of the probability parameters. Only the weights assigned to those alignments change. Therefore, if we know all the hits, we can easily (and quickly) find optimal seeds. We describe a highly efficient preprocessing step, which is computed just once for each seed. In this calculation, strings which represent possible alignments are unweighted by any probability parameters. Then we show several increasingly efficient methods to find the optimal seed when given specific probability parameters. Indeed, we show how to determine exactly which seeds can never be optimal under any set of probability parameters. This leads to the startling observation that out of thousands of seeds, only a handful have any chance of being optimal. We then show bow to find optimal seeds and the boundaries within probability space where they are optimal. We expect this method to greatly facilitate the study of seed space sensitivity, construction of multiple seed sets,

关键词： Probability

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Flow model of the protein-protein interaction network for finding credible interactions

Flow model of the protein-protein interaction network for fi...

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5th Asia-Pacific bioinformatics Conference (APBC2007)

作者： Okada, Kinya Asai, Kiyoshi Arita, Masanori Univ Tokyo Grad Sch Frontier Sci Dept Computat Biol 5-1-5 Kashiwanoha Kashiwa Chiba 2778561 Japan Natl Inst Adv Ind Sci & Technol Computat Biol Res Ctr Kashiwa Chiba 2778561 Japan Univ Tokyo Grad Sch Frontier Sci PRESTO JST Kashiwa Chiba 2778561 Japan Keio Univ Inst Adv Biosci Kashiwa Chiba 2778561 Japan

ISBN: (纸本)9781860947834

Large-scale protein-protein interactions (PPIs) detected by yeast-two-hybrid (Y2H) systems are known to contain many false positives. The separation of credible interactions from background noise is still an unavoidable task. In the present study, we propose the relative reliability score for PPI as an intrinsic characteristic of global topology in the PPI networks. Our score is calculated as the dominant eigenvector of an adjacency matrix and represents the steady state of the network flow. By using this reliability score as a cut-off threshold from noisy Y2H PPI data, the credible interactions were extracted with better or comparable performance of previously proposed methods which were also based on the network topology. The result suggests that the application of the network-flow model to PPI data is useful for extracting credible interactions from noisy experimental data.

关键词： Proteins

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Exact and heuristic approaches for identifying disease-associated SNP motifs

Exact and heuristic approaches for identifying disease-assoc...

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5th Asia-Pacific bioinformatics Conference (APBC2007)

作者： Huang, Gaofeng Jeavons, Peter Kwiatkowski, Dominic Univ Oxford Comp Lab Oxford England Univ Oxford Wellcome Trust Ctr Human Genet Oxford England

ISBN: (纸本)9781860947834

A Single Nucleotide Polymorphism (SNP) is a small DNA variation which occurs naturally between different individuals of the same species. Some combinations of SNPs in the human genome are known to increase the risk of certain complex genetic diseases. This paper formulates the problem of identifying such disease-associated SNP motifs as a combinatorial optimization problem and shows it to be NP-hard. Both exact and heuristic approaches for this problem are developed and tested on simulated data and real clinical data. computational results are given to demonstrate that these approaches are sufficiently effective to support ongoing biological research.

关键词： Heuristic methods

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Subtle motif discovery for detection of DNA regulatory sites

Subtle motif discovery for detection of DNA regulatory sites

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5th Asia-Pacific bioinformatics Conference (APBC2007)

作者： Comin, Matteo Univ Padua Dept Informat Engn Padua Italy

ISBN: (纸本)9781860947834

We address the problem of detecting consensus motifs, that occur with subtle variations, across multiple sequences. These are usually functional domains in DNA sequences such as transcriptional binding factors or other regulatory sites. The problem in its generality has been considered difficult and various benchmark data serve as the litmus test for different computational methods. We present a method centered around unsupervised combinatorial pattern discovery. The parameters are chosen using a careful statistical analysis of consensus motifs. This method works well on the benchmark data and is general enough to be extended to a scenario where the variation in the consensus motif includes indels (along with mutations). We also present some results on detection of transcription binding factors in human DNA sequences.

关键词： Binding sites Consensus motifs Pattern discovery Subtle motifs Transcription factors

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Protein structure-structure alignment with discrete frechet distance

Protein structure-structure alignment with discrete frechet ...

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5th Asia-Pacific bioinformatics Conference (APBC2007)

作者： Jiang, Minghui Xu, Ying Zhu, Binhai Utah State Univ Dept Comp Sci Logan UT 84322 USA Univ Georgia Dept Biochem & Mol Biol Athens GA 30602 USA Montana State Univ Dept Comp Sci Bozeman MT 59717 USA

ISBN: (纸本)9781860947834

Matching two geometric objects in 2D and 3D spaces is a central problem in computer vision, pattern recognition and protein structure prediction. In particular, the problem of aligning two polygonal chains under translation and rotation to minimize their distance has been studied using various distance measures. It is well known that the Hausdorff distance is useful for matching two point sets, and that the Frechet distance is a superior measure for matching two polygonal chains. The discrete Frechet distance closely approximates the (continuous) Frechet distance,and is a natural measure for the geometric similarity of the folded 3D structures of bio-molecules such as proteins. In this paper, we present new algorithms for matching two polygonal chains in 2D to minimize their discrete Frechet distance under translation and rotation, and an effective heuristic for matching two polygonal chains in 3D. We also describe our empirical results on the application of the discrete Frechet distance to the protein structure-structure alignment.

关键词： Pattern recognition

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