检索结果-内蒙古大学图书馆

DNA binding shapes upAssociated Content

Nature 2009年第7268期461卷 1225-1226页

作者： Tom Tullius Tom Tullius is in the Department of Chemistry and the Program in Bioinformatics Boston University Boston Massachusetts 02215 USA. tullius@bu.edu

来源：评论

学校读者我要写书评

暂无评论

Rank-based clustering analysis for the time-microarray data

引用

Journal of bioinformatics and Computational Biology 2009年第1期7卷 75-91页

作者： Yi, Sung-Gon Joo, Yoon-Jeong Park, Taesung Department of Statistics Seoul National University Seoul 151-742 San 56-1 Sillim-dong Gwanak-gu South Korea Program in Bioinformatics Seoul National University Seoul 151-742 San 56-1 Sillim-dong Gwanak-gu South Korea

Microarray technology allows the monitoring of expression levels for thousands of genes simultaneously. In time-course microarray experiments in which gene expression is monitored over time, we are interested in clustering genes that show similar temporal profiles and identifying genes that show a pre-specified candidate profile. Unfortunately, many traditional clustering methods used for analyzing microarray data do not effectively detect temporal profiles for the time-course microarray data. We propose a rank-based clustering analysis for the time-course microarray data. Our clustering method consists of two steps: the firststep discretizes the expression data into groups and then transform them into the rank data, the second step performs the rank-based clustering analysis. Our testing procedure uses the bootstrap samples to select the genes that show similar patterns for the candidate profiles. Simulation study is performed to evaluate the performance of the proposed rank-based method. The results are illustrated with the breast cancer data and the Arabidopsis cold stress data. © 2009 Imperial College Press.

关键词： Clustering Rank Time-course microarray

来源：评论

学校读者我要写书评

暂无评论

Inference of large-scale gene regulatory networks using regression-based network approach

引用

Journal of bioinformatics and Computational Biology 2009年第4期7卷 717-735页

作者： Kim, Haseong Lee, Jae K. Park, Taesung Interdisciplinary Program in Bioinformatics Seoul National University Seoul San 56-1 Shilim-dong South Korea Division of Biostatistics and Epidemiology University of Virginia Charlottesville VA 22908 United States Department of Statistics Seoul National University Seoul San 56-1 Shilim-dong South Korea

The gene regulatory network modeling plays a key role in search for relationships among genes. Many modeling approaches have been introduced to find the causal relationship between genes using time series microarray data. However, they have been suffering from high dimensionality, overfitting, and heavy computation time. Further, the selection of a best model among several possible competing models is not guaranteed that it is the best one. In this study, we propose a simple procedure for constructing large scale gene regulatory networks using a regression-based network approach. We determine the optimal out-degree of network structure by using the sum of squared coefficients which are obtained from all appropriate regression models. Through the simulated data, accuracy of estimation and robustness against noise are computed in order to compare with the vector autoregressive regression model. Our method shows high accuracy and robustness for inferring large-scale gene networks. Also it is applied to Caulobacter crecentus cell cycle data consisting of 1472 genes. It shows that many genes are regulated by two transcription factors, ctrA and gcrA, that are known for global regulators. © 2009 Imperial College Press.

关键词： Large-scale gene regulatory networks Linear regression Scale-free networks Weighted voting

来源：评论

学校读者我要写书评

暂无评论

Redesign of high-affinity nonspecific nucleases with altered sequence preference

引用

Journal of the American Chemical Society 2009年第47期131卷 17345-17353页

作者： Wang, Yi-Ting Wright, Jon D. Doudeva, Lyudmila G. Jhang, Hua-Ci Lim, Carmay Yuan, Hanna S. Institute of Molecular Biology Academia Sinica Taipei Taiwan Institute of Biomedical Sciences Academia Sinica Taipei Taiwan Institute of Chemical Biology and Molecular Biophysics Taiwan International Graduate Program Academia Sinica Taipei Taiwan Institute of Bioinformatics and Structural Biology Department of Chemistry National Tsing Hua University HsinChu Taiwan Institute of Biochemistry and Molecular Biology National Taiwan University Taipei Taiwan

It is of crucial importance to elucidate the underlying principles that govern the binding affinity and selectivity between proteins and DNA. Here we use the nuclease domain of Colicin E7 (nColE7) as a model system to generate redesigned nucleases with improved DNA-binding affinities. ColE7 is a bacterial toxin, bearing a nonspecific endonuclease domain with a preference for hydrolyzing DNA phosphodiester bonds at the 3O-side after thymine and adenine;i.e., it prefers Thy and Ade at the -1 site. Using systematic computational screening, six nColE7 mutants were predicted to bind DNA with high affinity. Five of the redesigned single-point mutants were constructed and purified, and four mutants had a 3- to 5-fold higher DNA binding affinity than wild-type nColE7 as measured by fluorescence kinetic assays. Moreover, three of the designed mutants, D493N, D493Q, and D493R, digested DNA with an increased preference for guanine at +3 sites compared to the wild-type enzyme, as shown by DNA footprint assays. X-ray structure determination of the ColE7 mutant D493Q-DNA complex in conjunction with structural and free energy decomposition analyses provides a physical basis for the improved protein-DNA interactions: Replacing D493 at the protein-DNA interface with an amino acid residue that can maintain the native hydrogen bonds removes the unfavorable electrostatic repulsion between the negatively charged carboxylate and DNA phosphate groups. These results show that computational screening combined with biochemical, structural, and free energy analyses provide a useful means for generating redesigned nucleases with a higher DNA-binding affinity and altered sequence preferences in DNA cleavage. © 2009 American Chemical Society.

关键词： DNA

来源：评论

学校读者我要写书评

暂无评论

Structural insights into TDP-43 in nucleic-acid binding and domain interactions

引用

Nucleic Acids Research 2009年第6期37卷 1799-1808页

作者： Kuo, Pan-Hsien Doudeva, Lyudmila G. Wang, Yi-Ting Shen, Che-Kun James Yuan, Hanna S. Institute of Bioinformatics and Structural Biology National Tsing Hua University Taipei Taiwan Institute of Molecular Biology National Taiwan University Taipei Taiwan Taiwan International Graduate Program Chemical Biology and Molecular Biophysics National Taiwan University Taipei Taiwan Graduate Institute of Biochemistry and Molecular Biology National Taiwan University Taipei Taiwan

TDP-43 is a pathogenic protein: its normal function in binding to UG-rich RNA is related to cystic fibrosis, and inclusion of its C-terminal fragments in brain cells is directly linked to frontotemporal lobar degeneration (FTLD) and amyotrophic lateral sclerosis (ALS). Here we report the 1.65 Å crystal structure of the C-terminal RRM2 domain of TDP-43 in complex with a single-stranded DNA. We show that TDP-43 is a dimeric protein with two RRM domains, both involved in DNA and RNA binding. The crystal structure reveals the basis of TDP-43's TG/ UG preference in nucleic acids binding. It also reveals that RRM2 domain has an atypical RRM-fold with an additional β-strand involved in making protein-protein interactions. This self association of RRM2 domains produced thermal-stable RRM2 assemblies with a melting point greater than 85°C as monitored by circular dichroism at physiological conditions. These studies thus characterize the recognition between TDP-43 and nucleic acids and the mode of RRM2 self association, and provide molecular models for understanding the role of TDP-43 in cystic fibrosis and the neurodegenerative diseases related to TDP-43 proteinopathy. © 2009 The Author(s).

关键词：

来源：评论

学校读者我要写书评

暂无评论

A pathway analysis applied to Genetic Analysis Workshop 16 genome-wide rheumatoid arthritis data

引用

BMC proceedings 2009年第7期3 Suppl 7卷 S91页

作者： David H Ballard Chatchawit Aporntewan Ji Young Lee Joon Sang Lee Zheyang Wu Hongyu Zhao Program in Computational Biology and Bioinformatics Yale University 300 George Street Suite 503 New Haven Connecticut 06511 USA. david.ballard@yale.edu.

The identification of several hundred genomic regions affecting disease risk has proven the ability of genome-wide association studies have proven their ability to identify genetic contributors to disease. Currently, single-nucleotide polymorphism (SNP) association analysis is the most widely used method of genome-wide association data, but recent research shows that multi-marker tests of association may provide greater power, especially when more than one mutation is present within a gene and the mutations are in low linkage disequilibrium with each other. Here we use a multi-marker association test based on regression to SNPs located within known genes to obtain a gene-level score of association. We then perform pathway analysis using this score as a measure of gene importance. We use two tests of pathway enrichment - a binomial test and a random set method. By utilizing publicly available gene and pathway information, we identify B cell, cytokine and inflammation response, and antigen presentation pathways as being associated with rheumatoid arthritis. These results confirm known biological mechanisms for auto-immunity disorders, of which rheumatoid arthritis is one.

关键词： Rheumatoid Arthritis Major Histocompatibility Complex Major Histocompatibility Complex Class Binomial Test Gene Score

来源：评论

学校读者我要写书评

暂无评论

Purification and characterization of thermostable monomeric chloroplastic Cu/Zn superoxide dismutase from Chenopodium murale

引用

Physiology and Molecular Biology of Plants 2009年第3期15卷 199-209页

作者： Sundaram, Sabarinath Khanna, Sunil Khanna-Chopra, Renu Water Technology Centre Indian Agricultural Research Institute New Delhi 110 012 India Department of Biotechnology and Bioinformatics NIIT Institute of Information Technology (TNI) New Delhi 110 019 NIIT House Balaji Estate Kalkaji India Plant Molecular Biology Program Horticultural Sciences Department University of Florida Gainesville FL 32611-0690 United States

Superoxide dismutase is the first line of defense against oxidative stress and thus helps in maintaining the cellular integrity. Chenopodium murale, a weed species adapted to widely varying climatic conditions faces extremes of temperatures ranging from 4 °C to 45 °C (Tmax) during growth and development. From this plant, we have purified a thermostable chloroplastic Cu/Zn superoxide dismutase (Chl Cu/Zn SOD) to homogeneity using minimal steps. Incubation of lysed chloroplasts at 70 °C for 1h reduced the interference of cytosolic SOD isoforms and reduced the protein content by 75 %. Chloroplastic SOD was purified from the heat stable fraction by gel filtration chromatography. The purified enzyme had a native molecular weight of 24 kDa, a half-life of 47.9 min at 80 °C and showed a single band at 24 kDa on SDS-PAGE. The N-terminus contained the conserved amino acids of chl Cu-Zn SOD. The Chl Cu/Zn SOD protein and its activity were enhanced under very high temperatures, high light intensities and in water stress/recovered C. murale plants under controlled environment conditions. Chl Cu/Zn SOD was also one of the predominant isoforms throughout growing period in field grown plants and declined during senescence. The Chl Cu/Zn SOD activity increased with the increase in ambient temperature and peaked in April with a 45 °C Tmax. These results clearly indicate that the chloroplastic Cu/Zn SOD is stably expressed at extreme environmental conditions. The presence of stable monomeric chloroplastic Cu/Zn SOD might help the plants to maintain the cellular homeostatis against adverse environmental conditions. © Prof. H.S. Srivastava Foundation for Science and Society 2009.

关键词： Chenopodium Chloroplast Cu/Zn SOD Monomer Thermostable

来源：评论

学校读者我要写书评

暂无评论

An approach to comparing tiling array and high throughput sequencing technologies for genomic transcript mapping

引用

BMC Research Notes 2009年第1期2卷 1-7页

作者： Sasidharan, Rajkumar Agarwal, Ashish Rozowsky, Joel Gerstein, Mark Molecular Biophysics and Biochemistry Department Yale University New Haven CT 06520 United States Department of Plant Biology Carnegie Institution for Science Stanford CA 94305 United States Interdepartmental Program in Computational Biology and Bioinformatics Yale University New Haven CT 06520 United States Department of Computer Science Yale University New Haven CT 06520 United States

Background. There are two main technologies for transcriptome profiling, namely, tiling microarrays and high-throughput sequencing. Recently there has been a tremendous amount of excitement about the latter because of the advent of next-generation sequencing technologies and its promises. Consequently, the question of the moment is how these two technologies compare. Here we attempt to develop an approach to do a fair comparison of transcripts identified from tiling microarray and MPSS sequencing data. Findings. This comparison is a challenging task because the sequencing data is discrete while the tiling array data is continuous. We use the published rice and Arabidopsis datasets which provide currently best matched sets of arrays and sequencing experiments using a slightly earlier generation of sequencing, the MPSS tag sequencing technology. After scoring the arrays consistently in both the organisms, a first pass comparison reveals a surprisingly small overlap in transcripts of 22% and 66% respectively, in rice and Arabidopsis. However, when we do the analysis in detail, we find that this is an underestimate. In particular, when we map the probe intensities onto the sequencing tags and then look at their intensity distribution, we see that they are very similar to exons. Furthermore, restricting our comparison to only protein-coding gene loci revealed a very good overlap between the two technologies. Conclusion. Our approach to compare genome tiling microarray and MPSS sequencing data suggests that there is actually a reasonable overlap in transcripts identified by the two technologies. This overlap is distorted by the scoring and thresholding in the tiling array scoring procedure. © 2009 Sasidharan et al;licensee BioMed Central Ltd.

关键词： Tiling Array Transcript Mapping Tile Path Tiling Microarray Intergenic Transcript

来源：评论

学校读者我要写书评

暂无评论

Elastic-net regularization approaches for genome-wide association studies of rheumatoid arthritis

引用

BMC proceedings 2009年第7期3 Suppl 7卷 S25页

作者： Seoae Cho Haseong Kim Sohee Oh Kyunga Kim Taesung Park Interdisciplinary Program in Bioinformatics Seoul National University Kwan-ak St 599 Kwan-ak Gu Seoul South Korea 151-741 Republic of Korea. sacho71@snu.ac.kr.

The current trend in genome-wide association studies is to identify regions where the true disease-causing genes may lie by evaluating thousands of single-nucleotide polymorphisms (SNPs) across the whole genome. However, many challenges exist in detecting disease-causing genes among the thousands of SNPs. Examples include multicollinearity and multiple testing issues, especially when a large number of correlated SNPs are simultaneously tested. Multicollinearity can often occur when predictor variables in a multiple regression model are highly correlated, and can cause imprecise estimation of association. In this study, we propose a simple stepwise procedure that identifies disease-causing SNPs simultaneously by employing elastic-net regularization, a variable selection method that allows one to address multicollinearity. At Step 1, the single-marker association analysis was conducted to screen SNPs. At Step 2, the multiple-marker association was scanned based on the elastic-net regularization. The proposed approach was applied to the rheumatoid arthritis (RA) case-control data set of Genetic Analysis Workshop 16. While the selected SNPs at the screening step are located mostly on chromosome 6, the elastic-net approach identified putative RA-related SNPs on other chromosomes in an increased proportion. For some of those putative RA-related SNPs, we identified the interactions with sex, a well known factor affecting RA susceptibility.

关键词： Genetic Analysis Workshop Screen Step Ridge Penalty Autocrine Motility Factor Receptor Automatic Variable Selection

来源：评论

学校读者我要写书评

暂无评论

Genome-wide analysis of haplotype interaction for the data from the North American Rheumatoid Arthritis Consortium

引用

BMC proceedings 2009年第7期3 Suppl 7卷 S34页

作者： Jungsun Park Junghyun Namkung Mina Jhun Taesung Park Interdisciplinary Program in Bioinformatics Seoul National University San56-l Shin Lim-Dong Kwan Ak-Ku Seoul 151-747 Republic of Korea. pj518@snu.ac.kr.

Recent genome-wide association studies on several complex diseases have focused on individual single-nucleotide polymorphism (SNP) analysis; however, not many studies have reported interactions among genes perhaps because the gene-gene and gene-environment interaction analysis could be infeasible due to heavy computing requirements. In this study we propose a new strategy for exploring the interactions among haplotypes. The proposed method consists of two steps. Step 1 tests the single-SNP association of whole genome with multiple testing corrections and finds the haplotype blocks of the significant SNPs. Step 2 performs interaction analysis of haplotypes within blocks. Our proposed method is applied to the rheumatoid arthritis data for Genetic Analysis Workshop 16.

关键词： Haplotype Block Significant SNPs Codominant Model North American Rheumatoid Arthritis Consortium Haplotype Association Analysis

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：