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检索条件"任意字段=Proceedings - 2004 IEEE Computational Systems Bioinformatics Conference, CSB 2004"

共 372 条记录，以下是341-350 订阅

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Probe design for large-scale molecular biology applications

Probe design for large-scale molecular biology applications

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ieee conference on bioinformatics

作者： V. VanBuren T. Yoshikawa T. Hamatani M.S.H. Ko Laboratory of Genetics Developmental Genomics and Aging Section National Institute on Aging National Institutes of Health Baltimore MD USA

Large-scale molecular biology technologies such as DNA microarrays and large-scale in situ hybridization (ISH) are used to gain an appreciation of global attributes in biological tissues and cells. Although many of these efforts use cDNA probes, an approach that makes use of designed oligo probes should offer improved consistency at uniform hybridization conditions and improved specificity, as demonstrated by various oligo microarray platforms. We describe a new Web-based application that takes FASTA-formatted sequences as input, and returns both a list of the best choices for probes and a full report containing possible alternatives. Probe design for microarrays may use a scoring routine that optimizes probe intensity based upon an artificial neural network (ANN) trained to predict the average probe intensity from the physical properties of the probe and a screen for possible cross-reactivity. This new tool should provide a reliable way to construct probes that maximize signal intensity while minimizing cross-reactivity.

关键词： Probes Large-scale systems DNA Artificial neural networks Sequences Aging bioinformatics Cells (biology) Laboratories Genetics

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Development of a massively-parallel, biological circuit simulator

Development of a massively-parallel, biological circuit simu...

引用

ieee conference on bioinformatics

作者： R.L. Schiek E.E. May Computational Sciences & Computational Biology Sandia National Laboratories Albuquerque NM USA

Genetic expression and control pathways can be successfully modeled as electrical circuits. Given the vast quantity of genomic data, very large and complex genetic circuits can be constructed. To tackle such problems, the massively-parallel, electronic circuit simulator, Xyce/sup /spl trade//, is being adapted to address biological problems. Unique to this biocircuit simulator is the ability to simulate not just one or a set of genetic circuits in a cell, but many cells and their internal circuits interacting through a common environment. Currently, electric circuit analogs for common biological and chemical machinery have been created. Using such analogs, one can construct expression, regulation and reaction networks. Individual species can be connected to other networks or cells via nondiffusive or diffusive channels (i.e. regions where species diffusion limits mass transport). Within any cell, a hierarchy of networks may exist operating at different time-scales to represent different aspects of cellular processes. Though under development, this simulator can model interesting biological and chemical systems. Prokaryotic genetic and metabolic regulatory circuits have been constructed and their interactions simulated for Escherichia coli's tryptophan biosynthesis pathway. Additionally, groups of cells each containing an internal reaction network and communicating via a diffusion limited environment can produce periodic concentration waves. Thus, this biological circuit simulator has the potential to explore large, complex systems and environmentally coupled problems.

关键词： Biological system modeling Circuit simulation Genetics Chemicals Genomics bioinformatics Electronic circuits Machinery Cellular networks Amino acids

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Haplotype pattern mining & classification for detecting disease associated site

Haplotype pattern mining & classification for detecting dise...

引用

ieee conference on bioinformatics

作者： T. Kido M. Baba H. Matsumine Y. Higashi H. Higuchi M. Muramatsu JowareHanzomon 2F HuBit Genomix Inc. Tokyo Japan NTT Data Company Limited Tokyo Japan School of Biomedical Science Tokyo Medical and Dental University Tokyo Japan

Finding the causative genes for common diseases using SNP (single nucleotide polymorphism) markers is now becoming a real challenge. Although traditional statistical SNP association tests exist, these tests could not explain the effects of SNP combinations or probable recombination histories from ancestral chromosomes. Haplotype analysis of disease associated site provides more powerful markers than individual SNP analysis, and can help identify probable causative mutations. In this paper, we introduce a new method for effective haplotype pattern mining to detect disease associated mutations. Using this procedure, we can discover some of the new disease associated SNPs, which can not be detected by traditional methods. We will introduce a powerful tool for implementing this procedure with some worked examples.

关键词： Diseases Genetic mutations Testing Phylogeny Tree graphs Frequency estimation Genomics bioinformatics Poles and towers Dentistry

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Using rule induction methods to analyze gene expression data

Using rule induction methods to analyze gene expression data

引用

ieee conference on bioinformatics

作者： G. Livingston X. Li G. Li L. Hao J. Zhou University of Massachusetts Lowell USA

We have applied rule induction to a publicly available adenocarcinoma gene expression data set. The typical approach to the analysis of gene expression data is to cluster the genes. However, interpreting the resulting clusters may be difficult. With rules, the interpretation is more obvious (e.g., (CDKN3>253)/spl rarr/(tumor-stage=3)). Our rule induction tool is a new semiautonomous discovery system we are developing called HAMB, and we used it to learn rules for survival status, survival time, and tumor stage. When we searched the world-wide web for publications relating our top 53 genes from our discovered rules to lung cancer, we found that 9 of them are known to be associated with lung cancer, 19 of them are known to be associated with other types of cancer, and the remaining 25 were not known to be associated with cancer. Our results suggest that the latter two groups of genes should be examined more closely for their association with lung cancer.

关键词： Data analysis Gene expression Cancer Data mining Filtering Induction generators Lung neoplasms Genetic mutations Demography bioinformatics

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Aligning ESTs to genome using multilayer unique makers

Aligning ESTs to genome using multilayer unique makers

引用

ieee conference on bioinformatics

作者： F.R. Hsu J.F. Chen Department of Information Technology Taichung Healthcare and Management University Taiwan

As more and more genomic sequences have been sequenced and rapid growing of number of EST (expressed sequence tag), we need very fast and efficient algorithms to align ESTs to genome. ESTs contain the exon/intron structure. Let G and E denote the given genome and the given EST sequence respectively. In order to reduce the time complexity, it is quite important to locate the position of E in G efficiently. A unique maker is a sequence appeared in G only once. We can locate the position of E in G by finding unique markers contained in E. The time complexity to align ESTs to genome grows rapidly when we use longer unique markers. In this paper, we propose a multi-layer unique marker method to align ESTs to genome. Our method has the benefit of both short and long unique markers. Our algorithm can also use to locate the position of single nucleotide polymorphism (SNP). Experimental result shows that our method is much faster than common tools such as SIM4 and BLAT.

关键词： Genomics bioinformatics Sequences DNA Microcomputers Humans Information technology Medical services Technology management Proteins

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A computational approach to reconstructing gene regulatory networks

A computational approach to reconstructing gene regulatory n...

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ieee conference on bioinformatics

作者： X. Deng H. Ali Department of Computer Science College of Information Science and Technology University of Nebraska Omaha Omaha NE USA

With the rapid accumulation of gene expression data in publicly accessible databases, computational study of gene regulation has become an obtainable goal Intrinsic to this task will be data mining tools for inferring knowledge from biological data. In this project, we have developed a new data mining technique in which we adapt the connectivity of a recurrent neural network model by indexing regulatory elements and including nonlinear interaction terms. The new technique reduces the number of parameters by O(n), therefore increasing the chance of recovering the underlying regulatory network. In order to fit the model from data, we have developed a genetic fitting algorithm with O(n) time complexity and that adapts the connectivity during the fitting process until a satisfactory fit is obtained. We have implemented this fitting algorithm and applied it to two data sets: rat central nervous system development (CNS) data with 112 genes, and yeast whole genome data with 2467 genes. With multiple runs of the fitting algorithm, we were able to efficiently generate a statistical pattern of the model parameters from the data. Because of its adaptive features, this method will be especially useful for reconstructing coarse-grained gene regulatory network from large scale or genome scale gene expression data sets.

关键词： Computer networks Biology computing Gene expression Data mining Genomics bioinformatics Databases Recurrent neural networks Biological system modeling Indexing

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TC-DB: an architecture for membrane transport protein analysis

TC-DB: an architecture for membrane transport protein analys...

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ieee conference on bioinformatics

作者： C.V. Tran N.M. Yang M.H. Saier Division of Biological Sciences University of California at San Diego La Jolla CA USA

TC-DB is a comprehensive relational database containing structural, functional and evolutionary information about transmembrane transport proteins. The database contains factual material extracted from more than 9000 references, covering approximately 3000 representative proteins, classified into over 400 families. TC-DB is the primary resource allowing access to the data upon which the TC system is based. The TC system has been adopted by the international union of biochemistry and molecular biology (IUBMB). The functional ontology developed for TC-DB provides an infrastructure to develop powerful queries that yield biological insight. The TC-DB website offers a number of software tools that facilitate the analysis of membrane transporters. Multiple avenues of access are supported by the web interface including classification drill-down, parametric searching, and full-text searching. TC-DB has been used for the annotation of transport proteins in newly sequenced genomes and provides tools to trace evolutionary pathways. The database as well as web services are accessible free of charge at http://tcdb. ucsd. edu.

关键词： Biomembranes Proteins Relational databases Biological materials Data mining Biochemistry Ontologies Software tools Genomics bioinformatics

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Preliminary wavelet analysis of genomic sequences

Preliminary wavelet analysis of genomic sequences

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ieee conference on bioinformatics

作者： J. Ning C.N. Moore J.C. Nelson Delaware Biotechnology Institute University of Delaware Newark DE USA Department of Mathematics Kansas State University Manhattan KS USA Department of Plant Pathology Kansas State University Manhattan KS USA

Large genome-sequencing projects have made urgent the development of accurate methods for annotation of DNA sequences. Existing methods combine ab inito pattern searches with knowledge gathered from comparison with sequence databases or from training sets of known genes. However, the accuracy of these methods is still far from satisfactory. In the present study, wavelet algorithms in combination with entropy method are being developed as an alternative way to determine gene locations in genomic DNA sequences. Wavelet methods seek periodicity present in sequences. A promising advantage of wavelets is their adaptivity to varying lengths of coding/noncoding regions. Moreover, the wavelet methods integrated with entropy method just search the information contents of the sequences, which do not need to be trained. The preliminary results show that the wavelet approach is feasible and may be better than some knowledge-dependent approaches based on a sample of genomic DNA sequences.

关键词： Wavelet analysis Genomics bioinformatics Sequences DNA Hidden Markov models Entropy Signal processing algorithms Charge carrier processes Concatenated codes

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Stepping up the pace of discovery: the genomes to life program

Stepping up the pace of discovery: the genomes to life progr...

引用

ieee conference on bioinformatics

作者： M. Frazier D. Thomassen A. Patrinos G. Johnson C.E. Oliver E. Uberbacher U.S. Department of Energy Office of Science Office of Biological and Environmental Research U.S. Department of Energy Office of Science Office of Advanced Scientific Computing Research Oak Ridge National Laboratory UT-Battelle Limited Liability Company

Genomes to Life (GTL), the U.S. Department of Energy Office of Science's systems biology program, focuses on environmental microbiology. Over the next 10 to 20 years, GTL's key goal is to understand the life processes of thousands of microbes and microbial systems in their native environments. This focus demands that we address huge gaps in knowledge, technology, computing, data capture and analysis, and systems-level integration. Distinguishing features include: (1) strategies for unprecedented, comprehensive, and high-throughput data collection; (2) advanced computing, mathematics, algorithms, and data-management technologies; (3) a focus on potential microbial capabilities to help solve energy and environmental challenges; and (4) new research and management models that link production-scale systems biology facilities in an accessible environment. This unprecedented opportunity to provide the scientific foundation for solving urgent problems in energy, global climate change, and environmental cleanup demands that we take bold steps to achieve a much faster, more efficient pace of biological discovery.

关键词： Genomics bioinformatics systems biology Biology computing Data analysis Mathematics Energy management Environmental management Technology management Biological system modeling

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CoMRI: a compressed multiresolution index structure for sequence similarity queries

CoMRI: a compressed multiresolution index structure for sequ...

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ieee conference on bioinformatics

作者： H. Sun O. Ozturk H. Ferhatosmanoglu Department of Computer and Information Science Ohio State Uinversity USA Ohio State University Columbus OH US Dept. of Comput. & Inf. Sci. Ohio State Univ. Columbus OH USA

In this paper, we present CoMRI, compressed multiresolution index, our system for fast sequence similarity search in DNA sequence databases. We employ virtual bounding rectangle (VBR) concept to build a compressed, grid style index structure. An advantage of grid format over trees is subsequence location information is given by the order of corresponding VBR in the VBR list. Taking advantage of VBRs, our index structure fits into a reasonable size of memory easily. Together with a new optimized multiresolution search algorithm, the query speed is improved significantly. Extensive performance evaluations on human chromosome sequence data show that VBRs save 80%-93% index storage size compared to MBRs (minimum bounding rectangles) and new search algorithm prunes almost all unnecessary VBRs which guarantees efficient disk I/O and CPU cost. According to the results of our experiments, the performance of CoMRI is at least 100 times faster than MRS which is another grid index structure introduced very recently.

关键词： Sequences DNA Indexes bioinformatics Genomics Spatial databases Multidimensional systems Multiresolution analysis Sun Biomedical computing

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