2005 IEEE Computational Systems Bioinformatics Conference - Workshops (CSBW'05)最新文献_第9页

Patterns of gene deletion following genome duplication in yeast 酵母基因组复制后基因缺失的模式

2005 IEEE Computational Systems Bioinformatics Conference - Workshops (CSBW'05) Pub Date : 2005-08-08 DOI: 10.1109/CSBW.2005.104

J. Byrnes, Wen-Hsiung Li

引用次数: 2

Current challenges in bioimage database design 生物图像数据库设计面临的挑战

2005 IEEE Computational Systems Bioinformatics Conference - Workshops (CSBW'05) Pub Date : 2005-08-08 DOI: 10.1109/CSBW.2005.47

Ambuj K. Singh, Arnab Bhattacharya, Vebjorn Ljosa

引用次数: 1

Which normalization method is best? A platform-independent biologically inspired quantitative comparison of normalization methods 哪种归一化方法是最好的?一个独立于平台的生物学启发的标准化方法的定量比较

2005 IEEE Computational Systems Bioinformatics Conference - Workshops (CSBW'05) Pub Date : 2005-08-08 DOI: 10.1109/CSBW.2005.142

E. Someren, M. Reinders

引用次数: 0

Structural genomics analysis of alternative splicing and its application in modeling structures of alternatively spliced variants 交替剪接的结构基因组学分析及其在交替剪接变异体结构建模中的应用

2005 IEEE Computational Systems Bioinformatics Conference - Workshops (CSBW'05) Pub Date : 2005-08-08 DOI: 10.1109/CSBW.2005.129

Peng Wang, Bo Yan, Jun-tao Guo, C. Hicks, Ying Xu

{"title":"Structural genomics analysis of alternative splicing and its application in modeling structures of alternatively spliced variants","authors":"Peng Wang, Bo Yan, Jun-tao Guo, C. Hicks, Ying Xu","doi":"10.1109/CSBW.2005.129","DOIUrl":"https://doi.org/10.1109/CSBW.2005.129","url":null,"abstract":"Ii this paper we carry out a structural genomics analysis of known alternative splicing events and show that threading is a valid approach to model structures of alternatively spliced variants. We collect 3-D structures of proteins with know translated splicing products from PDB and further expand the dataset with high quality models generated with threading approach. Our analysis shows that splicing events have a strong preference for non-regular secondary structure elements and tend to avoid buried residues. Those observations suggest evolutionary constrains exist for locations of splicing in the context of 3-D environment. We then show that majority of substitutions in splicing events share high structural similarity and splicing events also tend to remove entire domain and avoid exposing hydrophobic cores when part of a domain was removed. Those observations support the notion that majority of splicing isoforms adopt same fold as full-length protein despite sequence substitutions and deletions. This principle was then utilized to generate high quality structures of splicing variants that could be a valuable resource for studying their structures and functions and may provide new insights into pathogenesis of related diseases.","PeriodicalId":123531,"journal":{"name":"2005 IEEE Computational Systems Bioinformatics Conference - Workshops (CSBW'05)","volume":"150 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122279921","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

cis-Regulatory element prediction in mammalian genomes 哺乳动物基因组的顺式调控元件预测

2005 IEEE Computational Systems Bioinformatics Conference - Workshops (CSBW'05) Pub Date : 2005-08-08 DOI: 10.1109/CSBW.2005.35

A. Siddiqui, Gordon Robertson, M. Bilenky, T. Astakhova, O. Griffith, M. Hassel, Keven Lin, S. Montgomery, M. Oveisi, E. Pleasance, Neil Robertson, M. Sleumer, Kevin Teague, R. Varhol, Maggie Zhang, Steven J. M. Jones

{"title":"cis-Regulatory element prediction in mammalian genomes","authors":"A. Siddiqui, Gordon Robertson, M. Bilenky, T. Astakhova, O. Griffith, M. Hassel, Keven Lin, S. Montgomery, M. Oveisi, E. Pleasance, Neil Robertson, M. Sleumer, Kevin Teague, R. Varhol, Maggie Zhang, Steven J. M. Jones","doi":"10.1109/CSBW.2005.35","DOIUrl":"https://doi.org/10.1109/CSBW.2005.35","url":null,"abstract":"The identification of cis-regulatory elements and modules is an important step in understanding the regulation of genes. We have developed a pipeline capable of running multiple motif prediction methods on a whole genome scale. Using gene expression datasets to identify co-expressed genes and the Ensemhl Compara database orthologues, we assemble input sequence sets comprised of the upstream regions of a target gene, its orthologues and co-expressed genes on the premise that such genes will share promoters by evolution (orthologues) or share regulatory control mechanisms (co-expressed genes). Co-expressed genes are identified by an approach that combines Pearson distances from multiple gene expression datasets derived from multiple experimental approaches and calibrated against the GO database. Our pipeline runs a number of established motif detection algorithms with a range of parameter settings on the input dataset. We integrate the diverse result sets by scoring motifs with a method-independent function. For each target gene, we assign p-values to the motif score by running the discovery pipeline on multiple sets of input sequence containing the target gene, non-coexpressed genes and \"Jake\" orthologues generated by neutral numerical evolution. We have predicted 30,636 motif binding sites in human for 4,182 genes and an initial set of 472 motif binding sites in mouse for 92 genes with p<0.001. The positive predictive value against a library of biologically confirmed regulatory sites approaches 0.4 at the highest p-value threshold. Predicted regulatory elements and other resources from the project are available at www.cisred.org.","PeriodicalId":123531,"journal":{"name":"2005 IEEE Computational Systems Bioinformatics Conference - Workshops (CSBW'05)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126629240","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Adapting support vector machines to predict translation initiation sites in the human genome 应用支持向量机预测人类基因组翻译起始位点

2005 IEEE Computational Systems Bioinformatics Conference - Workshops (CSBW'05) Pub Date : 2005-08-08 DOI: 10.1109/CSBW.2005.18

R. Akbani, Stephen Kwek

引用次数: 5

Multivariate gene selection: does it help? 多变量基因选择:有帮助吗?

2005 IEEE Computational Systems Bioinformatics Conference - Workshops (CSBW'05) Pub Date : 2005-08-08 DOI: 10.1109/CSBW.2005.95

Carmen Lai, M. Reinders

{"title":"Multivariate gene selection: does it help?","authors":"Carmen Lai, M. Reinders","doi":"10.1109/CSBW.2005.95","DOIUrl":"https://doi.org/10.1109/CSBW.2005.95","url":null,"abstract":"When building predictors of disease state based on gene expression data, gene selection is performed in order to achieve a good performance and to identify a relevant subset of genes. Although several gene selection algorithms have been proposed, a fair comparison of the available results is very problematic. This mainly stems from two factors. First, the results are often biased, since the test set is in one way or another involved in training the predictor, resulting in optimistically biased performance estimates. Second, the published results are often based on a small number of relatively simple datasets. Therefore, no general applicative conclusions can be drawn. We therefore adopted an unbiased protocol to perform a fair comparison of state of the art multivariate and univariate gene selection techniques, in combination with a range of classifiers. Our conclusions are based on seven gene expression datasets, across many cancer types. Surprisingly, we could not detect any significant improvement of multivariate feature selection techniques over univariate approaches. We speculate on the possible causes of this finding, ranging from the small sample size problem to the particular nature of the multivariate gene dependencies.","PeriodicalId":123531,"journal":{"name":"2005 IEEE Computational Systems Bioinformatics Conference - Workshops (CSBW'05)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128310727","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

Large-scale drug function prediction by integrating QIS D/sup 2/ and biospice 整合QIS D/sup 2/和生物香料的大规模药物功能预测

2005 IEEE Computational Systems Bioinformatics Conference - Workshops (CSBW'05) Pub Date : 2005-08-08 DOI: 10.1109/CSBW.2005.84

Ying Zhao, Charles C. Zhou, I. Oglesby, Cliff Zhou

{"title":"Large-scale drug function prediction by integrating QIS D/sup 2/ and biospice","authors":"Ying Zhao, Charles C. Zhou, I. Oglesby, Cliff Zhou","doi":"10.1109/CSBW.2005.84","DOIUrl":"https://doi.org/10.1109/CSBW.2005.84","url":null,"abstract":"Quantum Intelligence System for Drug Discovery (QIS D/sup 2/) is a unique adaptive learning system designed to predict potential large-scale drug characteristics such as toxicity and efficacy. BioSpice is a set of software tools designed to represent and simulate cellular processes funded by DARPA. We show a QIS D/sup 2/ model is successfully trained, tested and validated on experimental data sets for predicting the potential in vivo effects of drug molecules in biological systems. QIS D/sup 2/ is interoperable with BioSpice. The workflow and visualization are built-in capabilities for easy-of-use. The integration of QIS D/sup 2/ and BioSpice draw on diversified technologies to deliver unique benefits for simulation and screening of potential drugs and their targets. We show that our approach leverages both structured and unstructured bioinformatics databases such as BioWarehouse and GeneWays in BioSpice to greatly enhance a QIS D/sup 2/ model. We show QIS D/sup 2/ models data from seven sources for 37,330 chemicals, performs an automatic sequence clustering using 1234 structure fragments, and accurately predict 1829 targets simultaneously.","PeriodicalId":123531,"journal":{"name":"2005 IEEE Computational Systems Bioinformatics Conference - Workshops (CSBW'05)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121742908","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Automatic protein function annotation through candidate ortholog clusters from incomplete genomes 通过来自不完整基因组的候选同源簇自动注释蛋白质功能

2005 IEEE Computational Systems Bioinformatics Conference - Workshops (CSBW'05) Pub Date : 2005-08-08 DOI: 10.1109/CSBW.2005.27

A. Vashist, C. Kulikowski, I. Muchnik

引用次数: 1

Multispectral multidimensional multiplexed data: the more, the merrier 多光谱多维复用数据:越多越好

2005 IEEE Computational Systems Bioinformatics Conference - Workshops (CSBW'05) Pub Date : 2005-08-08 DOI: 10.1109/CSBW.2005.94

R. Levenson, C. Hoyt, J. Mansfield, K. Gossage

{"title":"Multispectral multidimensional multiplexed data: the more, the merrier","authors":"R. Levenson, C. Hoyt, J. Mansfield, K. Gossage","doi":"10.1109/CSBW.2005.94","DOIUrl":"https://doi.org/10.1109/CSBW.2005.94","url":null,"abstract":"The ability to detect multiple molecular species at once is becoming increasingly important. Multispectral imaging systems can be used to capture multiplexed molecular signals, and can be applied to the analysis of chromogenically stained slides in brightfield mode and of samples stained with a variety of light-emitting dyes (from the visible to the NIR range) in fluorescence mode. Quantum dots make a particularly good match with this imaging technology, which is also extremely helpful for the identification and elimination of interfering autofluorescence. The ability to accurately determine the spectral qualities of dyes in-situ is also valuable. Multispectral imaging has proven to be useful for multicolor FISH, for resolving multiple species of GFP with overlapping emission spectra and for resolving red/brown double-labeled histopathology stains. The uses of spectral imaging in clinical pathology are still being explored and need to be matched to appropriate software tools. Appropriately constrained linear unmixing algorithms and novel automated tools have recently been developed to provide simple, accurate analysis procedures. Conventional hematoxylin-and-eosin-or Papanicolaou-stained pathology sections can have sufficient spectral content to allow the classification of cells of different lineage or to separate normal from neoplastic cells. Analysis of such specimens may succeed using spectral \"signatures\" and simple segmentation algorithms. The rich data sets also reward the use of more advanced analysis techniques. These can include a number of approaches pioneered for remote sensing purposes, such as spectral similarity mapping, automated clustering algorithms in n dimensions, principal component analysis, as well as other more sophisticated techniques.","PeriodicalId":123531,"journal":{"name":"2005 IEEE Computational Systems Bioinformatics Conference - Workshops (CSBW'05)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115040190","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0