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Pathway mapping with operon information: an integer-programming method

Pathway mapping with operon information: an integer-programm...

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proceedings of the ieee computational systems bioinformatics conference, csb

作者： Fenglou Mao V. Olman Ying Xu Zhengchang Su D. Chuang Computational Systems Biology Lab Biochemistry & Molecular Biology Department Computational Biology Institute Oak Ridge National Laboratory University of Georgia USA

Biological pathway mapping is an important problem in the post-genomic era. We now present a new algorithm for pathway mapping in microbes. The algorithm considers not only sequence similarity among the template and target genes, but also the operon structures in the target genome. We formulated the mapping problem as a graph finding problem, and solved it by an integer-programming (IP) method. The goal is to minimize a linear object function subject to six constraints, such that maximal sequence similarity among the template and target genes are achieved, and at the same time, a minimal number of operons are covered in the target genome. Compared to our previous minimal spanning tree (MST) algorithm, the IP method has the following advantages: i) It is much faster and thus can map larger pathway involving a much large set of genes. ii) The IP method looks into the details of genes in the operons, and consequently avoids the many-to-one mapping mistakes that sometimes occur in the MST algorithm. We have compiled a large pathway training set to optimize the parameters of the program, and tested it by mapping 16 complex pathways from BioCyc onto *** K12 genome and the results are very promising.

关键词： Genomics bioinformatics Sequences computational systems biology Biochemistry computational biology Laboratories Testing Phylogeny Robustness

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A theoretical analysis of gene selection

A theoretical analysis of gene selection

引用

proceedings of the ieee computational systems bioinformatics conference, csb

作者： S. Mukherjee S.J. Roberts Department of Engineering Science University of Oxford Oxford UK

A great deal of recent research has focused on the challenging task of selecting differentially expressed genes from microarray data ('gene selection'). Numerous gene selection algorithms have been proposed in the literature, but it is often unclear exactly how these algorithms respond to conditions like small sample-sizes or differing variances. Choosing an appropriate algorithm can therefore be difficult in many cases. In this paper we propose a theoretical analysis of gene selection, in which the probability of successfully selecting relevant genes, using a given gene ranking function, is explicitly calculated in terms of population parameters. The theory developed is applicable to any ranking function which has a known sampling distribution, or one which can be approximated analytically. In contrast to empirical methods, the analysis can easily be used to examine the behaviour of gene selection algorithms under a wide variety of conditions, even when the numbers of genes involved runs into the tens of thousands. The utility of our approach is illustrated by comparing three well-known gene ranking functions.

关键词： Diseases Cells (biology) bioinformatics Data engineering Probability Sampling methods Algorithm design and analysis Data analysis Needles Testing

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Selection of putative cis-regulatory motifs through regional and global conservation

Selection of putative cis-regulatory motifs through regional...

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proceedings of the ieee computational systems bioinformatics conference, csb

作者： Youlian Pan B. Smith Hung Fang F.A. Famili M. Sikorska R. Walker Institute for Information Technology National Research Council Canada Ottawa ONT Canada Institute for Biological Sciences National Research Council Canada Ottawa ONT Canada

Cis-regulatory motifs are often overrepresented in promoters and may exhibit frequency biases in subpromoter regions (SPRs). Many probabilistic algorithms have been used to predict such motifs, but they tend to generate many false positives. We devised a novel algorithm, MotifFilter, that computes representation indices (RIs) for putative motifs. MotifFilter's RI is a ratio of the actual over expected frequency of a motif in promoters, SPRs or random genomic DNA that takes into account of the nucleotide probability distributions in these regions. This approach was applied to a genome-wide survey of putative cAMP-response elements (CREs) for motifs generated by a profile hidden Markov model. Twenty of 144 putative CRE motifs found in the survey were retained by the MotifFilter.

关键词： bioinformatics Genomics Sequences Frequency Hidden Markov models DNA Probability distribution Filtering algorithms Humans Information technology

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Whole genome sequencing, comparative genomics, and systems biology

Whole genome sequencing, comparative genomics, and systems b...

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proceedings of the ieee computational systems bioinformatics conference, csb

作者： E. Myers University of California Berkeley USA

The whole-genome shotgun sequencing method with paired end-reads has proven rapid and economical, producing high-quality reconstructions of Drosophila (2000), human (2001) and mouse (2001), in quick succession. We discuss the overall algorithmic strategy, the results one can expect by comparing the whole genome assembly of Drosophila against the recently finished sequence, and advances such as high-density solid state sequencing and single molecule detection systems. We anticipate having the euchromatic portions of the genomes of twelve species of Drosophila in the next year. We discuss the current state of the art in comparative gene finding, cis-control module finding, and possible improvements. The hope of these approaches is that we will be able to accurately identify the "parts lists" of the D. melanogaster genome, a basic prerequisite for systems biology. We conclude with a segment on the possibility of a program of high-throughput in-situ image analysis in Drosophila embryos. We describe what information we might collect and what we might be able to infer from it. It is our contention that this may be the best way to understand development from a systems perspective.

关键词： Genomics bioinformatics systems biology Image reconstruction Humans Mice Assembly systems Sequences Solid state circuits Image segmentation

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MISAE: a new approach for regulatory motif extraction

MISAE: a new approach for regulatory motif extraction

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proceedings of the ieee computational systems bioinformatics conference, csb

作者： Zhaohui Sun Jingyi Yang J.S. Deogun Department of Computer Science and Engineering University of Nebraska Lincoln Lincolnshire NE USA

The recognition of regulatory motifs of co-regulated genes is essential for understanding the regulatory mechanisms. However, the automatic extraction of regulatory motifs from a given data set of the upstream noncoding DNA sequences of a family of co-regulated genes is difficult because regulatory motifs are often subtle and inexact. This problem is further complicated by the corruption of the data sets. In this paper, a new approach called mismatch-allowed probabilistic suffix tree motif extraction (MISAE) is proposed. It combines the mismatch-allowed probabilistic suffix tree that is a probabilistic model and local prediction for the extraction of regulatory motifs. The proposed approach is tested on 15 co-regulated gene families and compares favorably with other state-of-the-art approaches. Moreover, MISAE performs well on "corrupted" data sets. It is able to extract the motif from a "corrupted" data set with less than one fourth of the sequences containing the real motif.

关键词： Sequences Data mining DNA Gene expression Predictive models Testing bioinformatics Sun Computer science Genomics

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A new hierarchical method for identification of dynamic regulatory pathways from time-series DNA microarray data

A new hierarchical method for identification of dynamic regu...

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proceedings of the ieee computational systems bioinformatics conference, csb

作者： A. Darvish E. Bak K. Gopalakrishhan R.H. Zadeh K. Najarian University of North Carolina at Charlotte USA College of Information Technology Electrical engineering Department Physics Department

A new hierarchical method is proposed to analyze timeseries DNA microarray data to identify dynamic genetic pathways. Initially the hierarchical method applies a specialized clustering technique to incorporate the available heuristic information about biological system. Then, the prototypes of the resulting clusters are used as time-variables to develop an auto regressive model to relate the expression of the prototypes to each other. The resulting model also allows the prediction of gene expressions for the next time steps. The developed AR model can then be used to relate the expression value of each single gene to the genes of other clusters. The proposed method was applied to the cell-cycle dataset containing the DNA microarray time-series of a large number of genes involved in the eukaryotic cell-cycle. The technique resulted to a network of interactions among five clusters of genes in which the genes of each cluster have a biologically-meaningful trend in time.

关键词： DNA computing bioinformatics

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Extracting characteristic patterns from genome-wide expression data by non-negative matrix factorization

Extracting characteristic patterns from genome-wide expressi...

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proceedings of the ieee computational systems bioinformatics conference, csb

作者： Nini Rao S.J. Shepherd School of Life Science and Technology University of Electronic Science and Technology Chengdu China School of Engineering Design and Technology University of Bradford Bradford UK

In this paper, we propose a novel approach, which is called as nonnegative matrix factorization (NMF), to analyze genome wide expression data. One of NMF advantages is that it can directly process these data without normalization. Firstly, we design an optimal algorithm for NMF approach. Compared with the existing NMF algorithms, our algorithm is more stable and converges very fast. We have coded the final algorithm in highly optimized C. Secondly, we describe the use of NMF in the extraction of the characteristic patterns from genome wide expression data. Thirdly, some simulation experiments are made in order to verify the efficiency of NMF algorithm, our conclusions are that NMF can be used as a powerful tool to extract the biologically-meaningful expression patterns from genomic wide expression data.

关键词： Data mining Genomics bioinformatics Signal processing algorithms Algorithm design and analysis Independent component analysis Noise reduction Gene expression Biological system modeling Biological information theory

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RepeatAssembler: a package for annotation of full-length repetitive DNA sequences in fungal genomes

RepeatAssembler: a package for annotation of full-length rep...

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proceedings of the ieee computational systems bioinformatics conference, csb

作者： M.L. Farman J.W. Jaromczyk J.W. Gilkerson C. Staben Department of Plant Pathology University of Kentucky USA Department of Computer Science University of Kentucky USA Department of Biology University of Kentucky USA

REPEATASSEMBLER aims to automate the identification of full-length consensus sequences for repetitive DNA fragments or the genetic material that is repeated many times throughout the genome (so-called repeats). Although there are packages with similar objectives, e.g. RECON, none fully meets the needs of researchers in comparative genomics. Joining short repeating elements into fall-length repeats is particularly intricate and handling this task properly is both the goal and the strength of our solution. REPEATASSEMBLER analyzes as few sequences as possible to screen out all repetitive sequences. Then it builds a set of non-redundant repeats and reports the full-length consensus sequence for each element in the set. REPEATASSEMBLER consistently delivers repetitive sequences that agree with known full-length repeats for several fungal genomes.

关键词： Packaging DNA Sequences Genomics bioinformatics Biological cells Genetics Biological materials Computer science Proteins

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High-throughput microarray-based genotyping

High-throughput microarray-based genotyping

引用

proceedings of the ieee computational systems bioinformatics conference, csb

作者： G. Yang Ming-Hsiu Ho E. Hubbell Affymetrix Inc.

A high throughput genotyping platform that scores over 10,000 single-nucleotide polymorphisms (SNPs) per individual on a single GeneChip/spl reg/ high-density oligonucleotide microarray has been developed to conduct studies to elucidate the genetic basis for complex diseases. Currently, the genotyping of individual SNPs relies on the summary statistics (based on the observed intensities of probes on the microarray) for the entirety of the sample set. A classification scheme of those statistics across hundreds of individual DNA samples is obtained to make individual genotyping calls. In contrast to the current approach, the method in this work makes individual genotyping call by finding the minimum residual, i.e. highest likelihood, among four possible states corresponding to three genotypes and no-call. Initially, the residual is calculated based on a given set of probe affinities for that individual sample. Auspiciously, the multitude of samples was utilized to iterate to refine the probe affinities, sample concentration, and background intensities. These refined parameters entail an improved call rate while maintaining high accuracy.

关键词： Probes Diseases Statistics Clustering algorithms Throughput Genetics DNA Robustness Frequency bioinformatics

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Functional modules from protein networks of kinome and cell cycle in Saccharomyces cerevisiae

Functional modules from protein networks of kinome and cell ...

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proceedings of the ieee computational systems bioinformatics conference, csb

作者： Hee Young Kang Hak Yong Kim Division of Life Sciences College of Natural Sciences Chungbuk National University South Korea

ISBN: (纸本)0769521940

We have constructed protein networks of kinome and cell cycle from MIPS database. The networks show character of scale free network, in which a few highly connected proteins play a central role in most cells. Protein-protein interaction database obtained from a yeast two hybrid screen or a composite data set includes random false positives. To purify the database, we employed cellular localization and DNA expression profile and then reconstructed kinome and cell cycle networks. The kinome and cell cycle networks constructed from the purified database show characters of scale free network and hierarchical network, in which preserves it's scale-free organization and displays inherent modularity of protein clusters. To find functional modules from the network, we propose a new technique that is based on multi-body correlations in kinome or cell cycle network. From the derived modules, we predicted and estimated tentative functions for unannotated proteins with high certainty.

关键词： Proteins Intelligent networks Databases Fungi DNA bioinformatics Genomics Cellular networks Educational institutions Displays

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