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PheGe, the platform for exploring genotype-phenotype relations on cellular and organism level 在细胞和有机体水平上探索基因型-表型关系的平台
Proceedings. IEEE Computer Society Bioinformatics Conference Pub Date : 2002-08-14 DOI: 10.1109/CSB.2002.1039331
K. Seidl
{"title":"PheGe, the platform for exploring genotype-phenotype relations on cellular and organism level","authors":"K. Seidl","doi":"10.1109/CSB.2002.1039331","DOIUrl":"https://doi.org/10.1109/CSB.2002.1039331","url":null,"abstract":"One major challenge of bioinformatics is to extract biological information into a form that gives access to analyses and predictive models and that sheds new light on cellular and organism function. In order to approach automated network analysis on organism level the relational platform PheGe was generated. PheGe enables (a) presentation of cell-specific regulatory and metabolic pathways, (b) sorting and coordination of the various molecules, genes and reactions to their particular signaling systems, (c) visualization of signaling par distance, (d) organization of downstream events on a multicellular level, (e) recording and evaluation of pathological relevant data, (f) coordination of the aberrant genes and gene products into the various regulatory pathways balancing phenotypic patterns (g) modeling of cellular differentiation and finally (h) tracing of network components that balance differentiation programs.","PeriodicalId":87204,"journal":{"name":"Proceedings. IEEE Computer Society Bioinformatics Conference","volume":"1 1","pages":"79-86"},"PeriodicalIF":0.0,"publicationDate":"2002-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/CSB.2002.1039331","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62213888","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: 2
Decoding noncoding regulatory DNAs in metazoan genomes 解码后生动物基因组中的非编码调控dna
Proceedings. IEEE Computer Society Bioinformatics Conference Pub Date : 2002-08-14 DOI: 10.1109/CSB.2002.1039323
Michele Markstein, A. Stathopoulos, Vicky Markstein, Peter W. Markstein, N. Harafuji, D. Keys, Byung-in Lee, P. Richardson, Daniel S. Rokshar, M. Levine
{"title":"Decoding noncoding regulatory DNAs in metazoan genomes","authors":"Michele Markstein, A. Stathopoulos, Vicky Markstein, Peter W. Markstein, N. Harafuji, D. Keys, Byung-in Lee, P. Richardson, Daniel S. Rokshar, M. Levine","doi":"10.1109/CSB.2002.1039323","DOIUrl":"https://doi.org/10.1109/CSB.2002.1039323","url":null,"abstract":"Summary form only given. The recent revelation that the human genome contains only /spl sim/30,000 genes underscores the importance of gene regulation in generating organismal diversity. Cis-regulatory DNAs, or enhancers, are short stretches of DNA-300 bp to 1,000 bp in length-that control gene expression. This DNA accounts for a substantial fraction of metazoan genomes, but is largely invisible. It cannot be identified by simple sequence inspection. One of the outstanding issues in the post-genome era is whether there is a \"cis-regulatory code\" that links primary DNA sequence with gene expression patterns. We have used a combination of bioinformatics methods and functional assays to determine whether coordinately regulated genes share a common \"grammar\".","PeriodicalId":87204,"journal":{"name":"Proceedings. IEEE Computer Society Bioinformatics Conference","volume":"1 1","pages":"5-"},"PeriodicalIF":0.0,"publicationDate":"2002-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/CSB.2002.1039323","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62214004","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
/spl Phi/LOG: a domain specific language for solving phylogenetic inference problems /spl Phi/LOG:用于解决系统发育推理问题的领域特定语言
Proceedings. IEEE Computer Society Bioinformatics Conference Pub Date : 2002-08-14 DOI: 10.1109/CSB.2002.1039324
Enrico Pontelli, D. Ranjan, B. Milligan, G. Gupta
{"title":"/spl Phi/LOG: a domain specific language for solving phylogenetic inference problems","authors":"Enrico Pontelli, D. Ranjan, B. Milligan, G. Gupta","doi":"10.1109/CSB.2002.1039324","DOIUrl":"https://doi.org/10.1109/CSB.2002.1039324","url":null,"abstract":"Domain experts think and reason at a high level of abstraction when they solve problems in their domain of expertise. We present the design and motivation behind a domain specific language (DSL), called /spl Phi/LOG, to enable biologists (domain experts) to program solutions to phylogenetic inference problems at a very high level of abstraction. The implementation infrastructure (interpreter, compiler, debugger) for the DSL is automatically obtained through a software engineering framework based on denotational semantics and logic programming.","PeriodicalId":87204,"journal":{"name":"Proceedings. IEEE Computer Society Bioinformatics Conference","volume":"1 1","pages":"9-20"},"PeriodicalIF":0.0,"publicationDate":"2002-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/CSB.2002.1039324","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62214039","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: 2
High similarity sequence comparison in clustering large sequence databases 聚类大序列数据库中的高相似性序列比较
Proceedings. IEEE Computer Society Bioinformatics Conference Pub Date : 2002-08-14 DOI: 10.1109/CSB.2002.1039345
Lorie Dudoignon, E. Glémet, H. C. Heus, M. Raffinot
{"title":"High similarity sequence comparison in clustering large sequence databases","authors":"Lorie Dudoignon, E. Glémet, H. C. Heus, M. Raffinot","doi":"10.1109/CSB.2002.1039345","DOIUrl":"https://doi.org/10.1109/CSB.2002.1039345","url":null,"abstract":"We present a fast algorithm for sequence clustering and searching which works with large sequence databases. It uses a strictly defined similarity measure. The algorithm is faster than conventional EST clustering approaches because its complexity is directly related to the number of subwords shared by the sequences. Furthermore, the algorithm also works with proteic sequences and large sequences like entire chromosomes. We present a theoretical study of our approach and provide experimental results.","PeriodicalId":87204,"journal":{"name":"Proceedings. IEEE Computer Society Bioinformatics Conference","volume":"1 1","pages":"228-236"},"PeriodicalIF":0.0,"publicationDate":"2002-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/CSB.2002.1039345","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62214448","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: 4
An adaptive meta-clustering approach: combining the information from different clustering results 一种自适应元聚类方法:结合不同聚类结果的信息
Proceedings. IEEE Computer Society Bioinformatics Conference Pub Date : 2002-08-14 DOI: 10.1109/CSB.2002.1039350
Yujing Zeng, Jianshan Tang, J. Garcia-Frías, G. Gao
{"title":"An adaptive meta-clustering approach: combining the information from different clustering results","authors":"Yujing Zeng, Jianshan Tang, J. Garcia-Frías, G. Gao","doi":"10.1109/CSB.2002.1039350","DOIUrl":"https://doi.org/10.1109/CSB.2002.1039350","url":null,"abstract":"With the development of microarray techniques, there is an increasing need for information processing methods to analyze high throughput data. Clustering is one of the most promising candidates because of its simplicity, flexibility and robustness. However, there is no \"perfect\" clustering approach outperforming its counterparts, and it is hard to evaluate and combine the results from different techniques, especially in a field without much prior knowledge, such as bioinformatics. This paper proposes a meta-clustering approach to extract information from results of different clustering techniques, so that a better interpretation of the data distribution can be obtained. A special distance measure is defined to represent the statistical \"signal\" of each cluster produced by various clustering techniques. The algorithm is applied to both artificial and real data Simulations show that the proposed approach is able to extract information efficiently and accurately from the input clustering structure.","PeriodicalId":87204,"journal":{"name":"Proceedings. IEEE Computer Society Bioinformatics Conference","volume":"1 1","pages":"276-287"},"PeriodicalIF":0.0,"publicationDate":"2002-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/CSB.2002.1039350","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62214645","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: 67
A Bayesian modeling framework for genetic regulation 遗传调控的贝叶斯建模框架
Proceedings. IEEE Computer Society Bioinformatics Conference Pub Date : 2002-08-14 DOI: 10.1109/CSB.2002.1039357
R. Khan, Yujing Zeng, J. Garcia-Frías, G. Gao
{"title":"A Bayesian modeling framework for genetic regulation","authors":"R. Khan, Yujing Zeng, J. Garcia-Frías, G. Gao","doi":"10.1109/CSB.2002.1039357","DOIUrl":"https://doi.org/10.1109/CSB.2002.1039357","url":null,"abstract":"We propose an integrated framework for model creation, execution, and validation in the context of modeling genetic regulatory networks. At the center of our framework is an executable model based on Bayesian networks (BNs). We use microarray data to infer how the expression of a gene is affected by all of the other genes. We create an execution model that predicts how the system will respond to a stimulus given an initial state. Our framework is validated using a Correct Answer Known Evaluator (CAKE). CAKE also allows us to investigate how much data and what kinds of data are needed to deduce the underlying interactions.","PeriodicalId":87204,"journal":{"name":"Proceedings. IEEE Computer Society Bioinformatics Conference","volume":"1 1","pages":"330-332"},"PeriodicalIF":0.0,"publicationDate":"2002-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62214331","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: 4
Distributions of free energy, melting temperature, and hybridization propensity for genomic DNA oligomers 基因组DNA低聚物的自由能分布、熔化温度和杂交倾向
Proceedings. IEEE Computer Society Bioinformatics Conference Pub Date : 2002-08-14 DOI: 10.1109/CSB.2002.1039360
R. Koehler, N. Peyret
{"title":"Distributions of free energy, melting temperature, and hybridization propensity for genomic DNA oligomers","authors":"R. Koehler, N. Peyret","doi":"10.1109/CSB.2002.1039360","DOIUrl":"https://doi.org/10.1109/CSB.2002.1039360","url":null,"abstract":"Many molecular biology techniques such as PCR, southern blotting, molecular beacon based assays, and DNA microarrays rely on the ability to design oligonucleotide probes possessing specific thermodynamic properties. Thermodynamic parameters for DNA duplex formation (melting temperature: Tm, free energy: /spl Delta/G/spl deg//sub /spl gamma//, and hybridization extent: Fb) are accurately predicted using the nearest-neighbor model for a range of physical conditions for oligonucleotides up to about 50 bases in length. The use of thermodynamic quantities is ubiquitous in probe design schemes, but invariably focus on achieving specific values for sequences in hand. This fails to provide general insights about how these quantities depend on sequence composition, length, and experimental conditions. Here we present Tm and Fb distributions calculated for genomic DNA samples of 10 to 50 bases.","PeriodicalId":87204,"journal":{"name":"Proceedings. IEEE Computer Society Bioinformatics Conference","volume":"1 1","pages":"337-"},"PeriodicalIF":0.0,"publicationDate":"2002-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/CSB.2002.1039360","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62214421","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: 2
A maximum entropy algorithm for rhythmic analysis of genome-wide expression patterns 全基因组表达模式节律性分析的最大熵算法
Proceedings. IEEE Computer Society Bioinformatics Conference Pub Date : 2002-08-14 DOI: 10.1109/CSB.2002.1039346
C. Langmead, C. Robertson, Mcclung Bruce, Randall Donald
{"title":"A maximum entropy algorithm for rhythmic analysis of genome-wide expression patterns","authors":"C. Langmead, C. Robertson, Mcclung Bruce, Randall Donald","doi":"10.1109/CSB.2002.1039346","DOIUrl":"https://doi.org/10.1109/CSB.2002.1039346","url":null,"abstract":"We introduce a maximum entropy-based analysis technique for extracting and characterizing rhythmic expression profiles from DNA microarray hybridization data. These patterns are clues to discovering genes implicated in cell-cycle, circadian, and other periodic biological processes. The algorithm, implemented in a program called ENRAGE (Entropy-based Rhythmic Analysis of Gene Expression), treats the task of estimating an expression profile's periodicity and phase as a simultaneous bicriterion optimization problem. Specifically, a frequency domain spectrum is reconstructed from a time-series of gene expression data, subject to two constraints: (a) the likelihood of the spectrum and (b) the Shannon entropy of the reconstructed spectrum. Unlike Fourier-based spectral analysis, maximum entropy spectral reconstruction is well suited to signals of the type generated in DNA microarray experiments. Our algorithm is optimal, running in linear time in the number of expression profiles. Moreover an implementation of our algorithm runs an order of magnitude faster than previous methods. Finally, we demonstrate that ENRAGE is superior to other methods at identifying and characterizing periodic expression profiles on both synthetic and actual DNA microarray hybridization data.","PeriodicalId":87204,"journal":{"name":"Proceedings. IEEE Computer Society Bioinformatics Conference","volume":"1 1","pages":"237-245"},"PeriodicalIF":0.0,"publicationDate":"2002-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/CSB.2002.1039346","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62214462","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: 27
MiCA: web-based computational tools for the analysis of microbial community structure and composition based on T-RFLP of 16S rRNA genes MiCA:基于16S rRNA基因T-RFLP分析微生物群落结构和组成的基于网络的计算工具
Proceedings. IEEE Computer Society Bioinformatics Conference Pub Date : 2002-08-14 DOI: 10.1109/CSB.2002.1039364
Conrad Shyu, J. Foster, K. Liao, S. Bent, K. Sale, L. Forney, Terence Soule
{"title":"MiCA: web-based computational tools for the analysis of microbial community structure and composition based on T-RFLP of 16S rRNA genes","authors":"Conrad Shyu, J. Foster, K. Liao, S. Bent, K. Sale, L. Forney, Terence Soule","doi":"10.1109/CSB.2002.1039364","DOIUrl":"https://doi.org/10.1109/CSB.2002.1039364","url":null,"abstract":"Analyses of microbial community structure based on terminal restriction fragment length polymorphisms (T-RFLP) of 16S rRNA genes are hindered by the lack of computational tools needed to aid experimental design, and to archive and analyze large data sets. The aim of this research was to develop a suite of Web-based tools that would enable researchers to perform several tasks, including: (a) in silico PCR amplification and restriction of 16S rRNA gene sequences found in public databases; (b) automatic retrieval of data and archival storage in an Oracle relational database; (c) comparison of multiple T-RFLP profiles obtained from a single sample using different primer-enzyme combinations; and (d) statistical analysis of T-RFLP data and clustering of samples based on similarities and differences.","PeriodicalId":87204,"journal":{"name":"Proceedings. IEEE Computer Society Bioinformatics Conference","volume":"1 1","pages":"341-"},"PeriodicalIF":0.0,"publicationDate":"2002-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/CSB.2002.1039364","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62214532","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: 2
An index structure for pattern similarity searching in DNA microarray data DNA微阵列数据模式相似性检索的索引结构
Proceedings. IEEE Computer Society Bioinformatics Conference Pub Date : 2002-08-14 DOI: 10.1109/CSB.2002.1039348
Haixun Wang, Chang-Shing Perng, W. Fan, Philip S. Yu
{"title":"An index structure for pattern similarity searching in DNA microarray data","authors":"Haixun Wang, Chang-Shing Perng, W. Fan, Philip S. Yu","doi":"10.1109/CSB.2002.1039348","DOIUrl":"https://doi.org/10.1109/CSB.2002.1039348","url":null,"abstract":"DNA microarray technology is about to bring an explosion of gene expression data that may dwarf even the human sequencing projects. Researchers are motivated to identify genes whose expression levels rise and fall coherently under a set of experimental perturbations, that is, they exhibit fluctuation of a similar shape when conditions change. In this paper, we show that queries based on pattern correlations against large-scale microarray databases can be supported by the weighted-sequence model, an index structure designed for sequence matching. A weighted-sequence is a two-dimensional structure where each element in the sequence is associated with a weight. We transform the DNA microarray data, as well as pattern-based queries, into weighted-sequences, and use subsequence matching algorithms to retrieve from the database all genes that match the query pattern. We demonstrate, using both synthetic and real-world data sets, that our method is effective and efficient.","PeriodicalId":87204,"journal":{"name":"Proceedings. IEEE Computer Society Bioinformatics Conference","volume":"22 1","pages":"256-267"},"PeriodicalIF":0.0,"publicationDate":"2002-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/CSB.2002.1039348","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62214571","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
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