2007 IEEE International Conference on Bioinformatics and Biomedicine Workshops最新文献_第3页

Multiresolution approaches to representation and visualization of large influenza virus sequence datasets 大型流感病毒序列数据集的多分辨率表示和可视化方法

2007 IEEE International Conference on Bioinformatics and Biomedicine Workshops Pub Date : 2007-11-01 DOI: 10.1109/BIBMW.2007.4425408

L. Zaslavsky, Yīmíng Bào, T. Tatusova

{"title":"Multiresolution approaches to representation and visualization of large influenza virus sequence datasets","authors":"L. Zaslavsky, Yīmíng Bào, T. Tatusova","doi":"10.1109/BIBMW.2007.4425408","DOIUrl":"https://doi.org/10.1109/BIBMW.2007.4425408","url":null,"abstract":"Rapid growth of the amount of genome sequence data requires enhancing exploratory analysis tools, with analysis being performed in a fast and robust manner. Users need data representations serving different purposes: from seeing overall structure and data coverage to evolutionary processes during a particular season. Our approach to the problem is in constructing hierarchies of data representations, and providing users with representations adaptable to specific goals. It can be done efficiently because the structure of a typical influenza dataset is characterized by low estimated values of the Kolmogorov (box) dimension. Multi-scale methodologies allow interactive visual representation of the dataset and accelerate computations by importance sampling. Our tree visualization approach is based on a subtree aggregation with subscale resolution. It allows interactive refinements and coarsening of subtree views. For importance sampling large influenza datasets, we construct sets of well-scattered points (e-nets). While a tree build for a global sample provides a coarse-level representation of the whole dataset, it can be complemented by trees showing more details in chosen areas. To reflect both global dataset structure and local details correctly, we perform local refinement gradually, using a multiscale hierarchy of e-nets. Our hierarchical representations allow fast metadata searching.","PeriodicalId":260286,"journal":{"name":"2007 IEEE International Conference on Bioinformatics and Biomedicine Workshops","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130142300","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

Are filter methods very effective in gene selection of microarray data? 过滤方法在微阵列数据的基因选择中是否非常有效?

2007 IEEE International Conference on Bioinformatics and Biomedicine Workshops Pub Date : 2007-11-01 DOI: 10.1109/BIBMW.2007.4425406

Zhou-Jun Li, Lijuan Zhang, Huo-Wang Chen

引用次数: 5

Point to face shortest paths in simple polytopes with applications in structural proteomics 在结构蛋白质组学中应用简单多面体的指向面最短路径

2007 IEEE International Conference on Bioinformatics and Biomedicine Workshops Pub Date : 2007-11-01 DOI: 10.1109/BIBMW.2007.4425394

O. Daescu, Y. Cheung

引用次数: 0

Non-quantized minimum free energy in untranslated region exons 非翻译区外显子的非量子化最小自由能

2007 IEEE International Conference on Bioinformatics and Biomedicine Workshops Pub Date : 1900-01-01 DOI: 10.1109/BIBMW.2007.4425397

K. Knapp, A. Rahaman, Y.-P.P. Chen

{"title":"Non-quantized minimum free energy in untranslated region exons","authors":"K. Knapp, A. Rahaman, Y.-P.P. Chen","doi":"10.1109/BIBMW.2007.4425397","DOIUrl":"https://doi.org/10.1109/BIBMW.2007.4425397","url":null,"abstract":"In an attempt to improve automated gene prediction in the untranslated region of a gene, we completed an in-depth analysis of the minimum free energy for 8,689 sub-genetic DNA sequences. We expanded Zhang's classification model and classified each sub-genetic sequence into one of 27 possible motifs. We calculated the minimum free energy for each motif to explore statistical features that correlate to biologically relevant sub-genetic sequences. If biologically relevant sub-genetic sequences fall into distinct free energy quanta it may be possible to characterize a motif based on its minimum free energy. Proper characterization of motifs can lead to greater understanding in automated genefinding, gene variability and the role DNA structure plays in gene network regulation. Our analysis determined: (1) the average free energy value for exons, introns and other biologically relevant sub-genetic sequences, (2) that these subsequences do not exist in distinct energy quanta, (3) that introns exist however in a tightly coupled average minimum free energy quantum compared to all other biologically relevant sub-genetic sequence types, (4) that single exon genes demonstrate a higher stability than exons which span the entire coding sequence as part of a multi-exon gene and (5) that all motif types contain a free energy global minimum at approximately nucleotide position 1,000 before reaching a plateau. These results should be relevant to the biochemist and bioinformatician seeking to understand the relationship between sub-genetic sequences and the information behind them.","PeriodicalId":260286,"journal":{"name":"2007 IEEE International Conference on Bioinformatics and Biomedicine Workshops","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124283487","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