检索结果-内蒙古大学图书馆

7th IEEE International Conference on bioinformatics and Bioengineering, BIBE

作者： Park, Chan-Hoon Kim, Soo-Jin Kim, Sun Cho, Dong-Yeon Zhang, Byoung-Tak School of Computer Science and Engineering Seoul National University Seoul 151-742 Korea Republic of Graduate Program in Bioinformatics Seoul National University Seoul 151-742 Korea Republic of

ISBN: (纸本)1424415098

High-throughput data such as microarrays make it possible to investigate the molecular-level mechanism of cancer more efficiently. Computational methods boost the microarray analysis by managing large and complex data systematically. However, combinatorial interactions among genes have not been considered as a unit of the analysis since previous methods mainly focus on a whole gene or a single isolated gene. Here, we introduce a molecular evolutionary algorithm called probabilistic library model (PLM). In the PLM, library elements are generated from gene combinations. An evolutionary procedure is adopted to learn the probabilistic distribution of training samples. We apply the PLM to prostate cancer microarray data. The experimental results show that the PLM classifiers perform better than conventional methods such as neural networks and decision trees in accuracy. We also examine the evolved library to find cancer-related gene combinations. ©2007 IEEE.

关键词： Microarrays

来源：评论

学校读者我要写书评

暂无评论

Finding pathway regulators: gene set approach using peak identification algorithms

引用

BMC proceedings 2007年第1期1 Suppl 1卷 S90页

作者： Eunjee Lee Jung Hoon Woo Ji Wan Park Taesung Park Interdisciplinary Program in Bioinformatics Seoul National University Seoul South Korea 151-747. eunjee01@***

Recently, a number of different approaches have been used to examine variation in gene expression and to identify genes whose level of transcript differed greatly among unrelated individuals. Previous studies have commonly focused on identifying determinants that regulate gene expressions by targeting individual genes. However, it is difficult to detect true differences in the level of gene expression among genotypes from noise due to issues such as multiple testing and limited sample size. To increase the statistical power for detecting this difference, we consider a 'gene set' approach by focusing on subtle but coordinated changes in gene expression across multiple genes rather than individual genes. We defined a 'gene set' as a set of genes in the same biological pathway and focused on identifying common regulators based on an assumption that the genes within the same pathway are controlled by common regulators. We applied the gene set approach to the expression data of mRNA in Centre d'Etude du Polymorphisme Humain lymphoblast cells to identify regulators controlling the genes in a biological pathway. Our gene set approach successfully identified potent regulators controlling gene expression in an inflammatory response pathway.

关键词： Significant Marker Common Regulator Common Peak Multipoint Linkage Analysis Significant eQTL

来源：评论

学校读者我要写书评

暂无评论

Analysis of Protein Protein Dimeric Interfaces

Analysis of Protein Protein Dimeric Interfaces

引用

IEEE International Conference on bioinformatics and Biomedicine (BIBM)

作者： Feihong Wu Fadi Towfic Drena Dobbs Vasant Honavar Bioinformatics and Computational Biology Graduate Program Iowa State University Ames IA USA

We analyzed the structural properties and the local surface environment of surface amino acid residues of proteins using a large, non-redundant dataset of 2383 protein chains in dimeric complexes from PDB. We compared the interface residues and non-interface residues based on six properties: side chain orientation, surface roughness, solid angle, ex value, hydrophobicity and interface cluster size. The results of our analysis show that interface residues have side chains pointing inward; interfaces are rougher, tend to be flat, moderately convex or concave and protrude more relative to non-interface surface residues. Interface residues tend to be surrounded by hydrophobic neighbors and tend to form clusters consisting of three or more interfaces residues. These findings are consistent with previous published studies using much smaller datasets, while allowing for more qualitative conclusions due to our larger dataset. Preliminary results suggest the possibility of using the six the properties to identify putative interface residues.

关键词： Proteins Rough surfaces Surface roughness bioinformatics Amino acids Solids Sequences Biomedical computing Computer interfaces Biomedical measurements

来源：评论

学校读者我要写书评

暂无评论

Refinement of under-determined loops of human prion protein by database-derived distance constraints

Refinement of under-determined loops of human prion protein ...

引用

IEEE International Conference on bioinformatics and Biomedicine Workshops (BIBMW)

作者： Feng Cui Kriti Mukhopadhyay Won-Bin Young Robert L. Jernigan Zhijun Wu Program on Bioinformatics and Computational Biology Department of Mathematics USA University Research Park Ames IA USA Department of Biochemistry Biophysics and Molecular Biology Iowa State University USA Program on Bioinformatics and Computational Biology USA

Computational simulations of the conversion from the normal cellular prion (PrP c ) to the scrapie prion (PrP Sc ) are usually based on the structures determined by NMR because of the difficulties in crystallizing prion protein. Due to insufficient experimental restraints, a biologically critical loop region in PrP c (residues 167-171), which is a potential binding site for Protein X, is under-determined in most mammalian species. Here, we show that by adding information about distance constraints derived from a database of high-resolution protein structures, this under-determined loop as well as other secondary structural elements of the E200K variant of human prion protein (hPrP c ), a disease-related isoform, can be refined into more realistic structures in the structural ensemble with improved quality and increased accuracy. In particular, the ensemble becomes more compact after the refinement and the percentage of residues in the most favourable region of the Ramachandran diagram is increased to about 90% in the refined structures from the 80 to 85% range in the previously reported structures. Our results not only provide significantly improved structures of the prion protein and hence would facilitate insights into its conversion in the spongiform encephalopathies, but also demonstrate the strong potential for using databases of known protein structures for structure determination and refinement.

关键词： Humans Proteins Databases Diseases Nuclear magnetic resonance Genetic mutations Computational biology Brain Pathogens Amino acids

来源：评论

学校读者我要写书评

暂无评论

eXpanda: An integrated platform for network analysis and visualization

引用

In Silico Biology 2007年第2期7卷 141-144页

作者： Negishi, Yoshiteru Nakamura, Hiroyuki Yachie, Nozomu Saito, Rintaro Tomita, Masaru Institute for Advanced Biosciences Keio University Fujisawa 252-8520 Japan Bioinformatics Program Graduate School of Media and Governance Keio University Fujisawa 252-8520 Japan Department of Environmental Information Keio University Fujisawa 252-8520 Japan

Analysis and visualization of biological networks, such as protein-protein and protein-DNA interactions, are crucially important toward obtaining a thorough understanding of living systems. Here, we present an integrative software platform, eXpanda, which enables an analysis of a very broad range of biological networks, with a special focus on the extraction of characteristic topologies which potentially function as units in the networks. eXpanda is provided as a Perl library which gives full-automatic connections to various biological databases via a Perl programmable interface and can perform topological analysis based on graph theory. The results of these analyses are visualizable by vector graphics. eXpanda is under GNU General Public License. Software package, detailed documentations, source codes, and some sample scripts are downloadable at http://***/expanda/. © 2007 IOS Press. All rights reserved.

关键词： Interactome Network analysis Network visualization Perl library Scalable Vector Graphics (SVG)

来源：评论

学校读者我要写书评

暂无评论

Evolving hypernetwork classifiers for microRNA expression profile analysis

Evolving hypernetwork classifiers for microRNA expression pr...

引用

Congress on Evolutionary Computation

作者： Sun Kim Soo-Jin Kim Byoung-Tak Zhang The Center for Bioinformatics Technology Graduate Program in Bioinformatics Seoul National University Seoul South Korea The School of Computer Science and Engineering Seoul National University Seoul South Korea

High-throughput microarrays inform us on different outlooks of the molecular mechanisms underlying the function of cells and organisms. While computational analysis for the microarrays show good performance, it is still difficult to infer modules of multiple co-regulated genes. Here, we present a novel classification method to identify the gene modules associated with cancers from microarray data. The proposed approach is based on 'hypernetworks', a hypergraph model consisting of vertices and weighted hyperedges. The hypernetwork model is inspired by biological networks and its learning process is suitable for identifying interacting gene modules. Applied to the analysis of microRNA (miRNA) expression profiles on multiple human cancers, the hypernetwork classifiers identified cancer-related miRNA modules. The results show that our method performs better than decision trees and naive Bayes. The biological meaning of the discovered miRNA modules has been examined by literature search.

关键词： Cancer Gene expression Biological system modeling Data analysis Support vector machines Support vector machine classification Evolutionary computation Humans Decision trees Diseases

来源：评论

学校读者我要写书评

暂无评论

RNAVLab: A unified environment for computational RNA structure analysis based on grid computing technology

RNAVLab: A unified environment for computational RNA structu...

引用

21st International Parallel and Distributed Processing Symposium, IPDPS 2007

作者： Taufer, M. Leung, M.-Y. Johnson, K.L. Licon, A. Dept. of Computer Science University of Texas El Paso Dept. of Mathematical Sciences University of Texas El Paso Dept. of Biological Sciences University of Texas El Paso Bioinformatics Program University of Texas El Paso

ISBN: (纸本)1424409101

Ribonucleic acid (RNA) molecules play important roles in many biological processes including gene expression and regulation. An RNA molecule is a linear polymer which folds back on itself to form a three dimensional (3D) functional structure. While experimental determination of precise 3D RNA structures is a time consuming and costly process, useful insight into the molecule can be gained from knowing its secondary structure. Structural elements in RNA secondary structures can be separated into two large categories: stem-loops and pseudoknots. The development of mathematical models and computational prediction algorithms for simple stem-loop structures started early in the 1980's. However, building systems that provide the tremendous computer time and memory needed for RNA analysis of both stem-loops and pseudoknots remains a challenge even today. The recently developed grid computing technology can offer a possible solution to this challenge. In this paper we briefly address mathematical problems associated with the grid computing approach to RNA structure prediction. In particular, we introduce models to partition a large RNA molecule into smaller segments to be assigned to different computers on the grid. Based on these models, we formulate a sampling strategy to select RNA segments for computational prediction to maximize prediction consistency. This strategy is under construction as part of RNAVLab, our unified environment for computational RNA structure analysis, i.e., prediction, alignment, comparison, and classification, A first prototype of RNAVLab is presented and used to investigate the possible association of secondary structure types with RNA functions by analyzing secondary structures for a family of nodavirus genomes. © 2007 IEEE.

关键词： Grid computing

来源：评论

学校读者我要写书评

暂无评论

Correcting base-assignment errors in repeat regions of shotgun assembly

Correcting base-assignment errors in repeat regions of shotg...

引用

作者： Zhi, Degui Keich, Uri Pevzner, Pavel Heber, Steffen Tang, Haixu Bioinformatics Program University of California San Diego San Diego CA 92093 Department of Computer Science 4130 Upson Hall Cornell University Ithaca NY 14853 Department of Computer Science and Engineering University of California San Diego San Diego CA 92093 North Carolina State University Raleigh NC 27695-7566 School of Informatics Center for Genomics and Bioinformatics Indiana University Bloomington IN 47408

Accurate base-assignment in repeat regions of a whole genome shotgun assembly is an unsolved problem. Since reads in repeat regions cannot be easily attributed to a unique location in the genome, current assemblers may place these reads arbitrarily. As a result, the base-assignment error rate in repeats is likely to be much higher than that in the rest of the genome. We developed an iterative algorithm, EULER-AIR, that is able to correct base-assignment errors in finished genome sequences in public databases. The Wolbachia genome is among the best finished genomes. Using this genome project as an example, we demonstrated that EULER-AIR can 1) discover and correct base-assignment errors, 2) provide accurate read assignments, 3) utilize finishing reads for accurate base-assignment and 4) provide guidance for designing finishing experiments. In the genome of Wolbachia, EULER-AIR found 16 positions with ambiguous base-assignment and two positions with erroneous bases. Besides Wolbachia, many other genome sequencing projects have significantly fewer finishing reads and, hence, are likely to contain more base-assignment errors in repeats. We demonstrate that EULER-AIR is a software tool that can be used to find and correct base-assignment errors in a genome assembly project. © 2007 IEEE.

关键词： Error analysis

来源：评论

学校读者我要写书评

暂无评论

The role of heritability in mapping expression quantitative trait loci

引用

BMC proceedings 2007年第1期1 Suppl 1卷 S86页

作者： Song Huang David Ballard Hongyu Zhao Program of Computational Biology and Bioinformatics Yale University New Haven Connecticut 06520 USA. song.huang@yale.edu

Gene expression, as a heritable complex trait, has recently been used in many genome-wide linkage studies. The estimated overall heritability of each trait may be considered as evidence of a genetic contribution to the total phenotypic variation, which implies the possibility of mapping genome regions responsible for the gene expression variation via linkage analysis. However, heritability has been found to be an inconsistent predictor of significant linkage signals. To investigate this issue in human studies, we performed genome-wide linkage analysis on the 3554 gene expression traits of 194 Centre d'Etude du Polymorphisme Humain individuals provided by Genetic Analysis Workshop 15. Out of the 422 expression traits with significant linkage signals identified (LOD > 5.3), 89 traits have low estimated heritability (h2 < 10%), among which 23 traits have an estimated heritability equal to 0. The linkage analysis on individual pedigree shows that the overall LOD scores may result from a few pedigrees with strong linkage signals. Screening gene expressions before linkage analysis using a relatively low heritability (h2 < 20%) may result in a loss of significant linkage signals, especially for trans-acting expression quantitative trait loci (49%).

关键词： Linkage Analysis Heritability Estimate Expression Trait Genetic Analysis Workshop Select Gene Expression

来源：评论

学校读者我要写书评

暂无评论

Structural characterization of RNA-binding sites of proteins: Preliminary results

Structural characterization of RNA-binding sites of proteins...

引用

IEEE International Conference on bioinformatics and Biomedicine Workshops (BIBMW)

作者： Fadi Towfic David C. Gemperline Cornelia Caragea Feihong Wu Drena Dobbs Vasant Honavar Bioinformatics and Computational Biology Graduate Program Iowa State University Ames IA USA Department of Biology Department of Chemistry Carthage College Kenosha WI USA Department of Computer Science Iowa State University Ames IA USA Department of Genetics Development and Cell Biology Bioinformatics and Computational Biology Graduate Program Iowa State University Ames IA USA Department of Computer Science Bioinformatics and Computational Biology Graduate Program Iowa State University Ames IA USA

We explore whether protein-RNA interfaces differ from non-interfaces in terms of their structural features and whether structural features vary according to the type of the bound RNA (e.g., mRNA, siRNA...etc), using a non-redundant dataset of 147 protein chains extracted from protein-RNA complexes in the protein data bank. Our analysis of surface roughness, solid angle and CX value of amino acid residues for each of the protein chains in the dataset shows that: The protein-RNA interface residues tend to be protruding compared to non-interface residues and tend to have higher surface roughness and exhibit moderately convex or concave solid angles. Furthermore, the protein chains in protein-RNA interfaces that contain Viral RNA and rRNA significantly differ from those that contain dsRNA, mRNA siRNA, snRNA, SRP RNA and tRNA with respect to their CX values. The results of this analysis sug gests the possibility of using such structural features to reliably identify protein-RNA interface residues when the structure of the protein is available but the structures of complexes formed by the protein with RNA are not.

关键词： RNA Protein engineering Biology computing Amino acids bioinformatics Computer interfaces Rough surfaces Surface roughness Solids Machine learning

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：